research paper on fingerprint analysis

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• Published: 19 May 2020

Collective intelligence in fingerprint analysis

• Jason M. Tangen 1 ,
• Kirsty M. Kent 1 &
• Rachel A. Searston 2  

Cognitive Research: Principles and Implications volume  5 , Article number:  23 ( 2020 ) Cite this article

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When a fingerprint is located at a crime scene, a human examiner is counted upon to manually compare this print to those stored in a database. Several experiments have now shown that these professional analysts are highly accurate, but not infallible, much like other fields that involve high-stakes decision-making. One method to offset mistakes in these safety-critical domains is to distribute these important decisions to groups of raters who independently assess the same information. This redundancy in the system allows it to continue operating effectively even in the face of rare and random errors. Here, we extend this “wisdom of crowds” approach to fingerprint analysis by comparing the performance of individuals to crowds of professional analysts. We replicate the previous findings that individual experts greatly outperform individual novices, particularly in their false-positive rate, but they do make mistakes. When we pool the decisions of small groups of experts by selecting the decision of the majority, however, their false-positive rate decreases by up to 8% and their false-negative rate decreases by up to 12%. Pooling the decisions of novices results in a similar drop in false negatives, but increases their false-positive rate by up to 11%. Aggregating people’s judgements by selecting the majority decision performs better than selecting the decision of the most confident or the most experienced rater. Our results show that combining independent judgements from small groups of fingerprint analysts can improve their performance and prevent these mistakes from entering courts.

Public Significance Statement

Several reports by peak scientific and regulatory bodies have been roundly critical of the dearth of evidence supporting traditional forensic methods and practices such as fingerprint analysis. In response to these criticisms, a number of experiments have now been conducted, demonstrating that professional fingerprint analysts are impressively accurate compared to novices when distinguishing between crime-scene prints from the same and different sources—but they still make mistakes. These mistakes are unavoidable, even in other high stakes, safety-critical domains such as medicine, aviation, or nuclear power. The aim, then, is to build safeguards into these systems that mitigate the impact of these mistakes in practice. In this experiment, we examine one such countermeasure, which exploits the collective intelligence of groups of professional fingerprint analysts. Our results show that pooling the decisions of small, independent groups of examiners can substantially boost the overall performance of these crowds and reduce the influence of errors. Integrating collective intelligence processes into existing forensic identification and verification systems could play a significant role—alongside effective training methods and evidence-based practices—in developing reliable and resilient systems to ensure the rule of law is justly applied.

When a fingerprint is recovered from a crime scene, a computer algorithm is used to compare the print to tens of millions of prints stored in a database. The algorithm then returns a list of potential candidates ranked from the most to the least similar. It is up to a human examiner to work through this list, comparing the overall pattern and flow of the prints as well as the fine details in each, such as ridge endings, bifurcations, contours, islands, dots, breaks, creases, pores, and enclosures. If the examiner has identified a sufficient number of corresponding features to be confident that the two prints came from the same person, then this final “same source” decision is logged into the computer system, which is then typically “verified” by a second examiner who—depending on their jurisdiction—may or may not be blind to the initial examiner’s decision (Thompson, Black, Jain, & Kadane, 2017 ).

Despite the fact that fingerprint examiners have been shown to perform exceptionally well (Searston & Tangen, 2017a ; Searston & Tangen, 2017b ; Tangen, Thompson, & McCarthy, 2011 ; Thompson & Tangen, 2014 ; Ulery, Hicklin, Buscaglia, & Roberts, 2011 ), errors have occurred in the past (Cole, 2005 ). A correct identification can mean the difference between exonerating a criminal or convicting an innocent person. It is clear that forensic analysts are working hard to capture criminals and uphold civil liberties; they have a very high workload, relentlessly coding evidence, supporting detectives, searching and maintaining databases, writing reports, and testifying as expert witnesses. It is also clear that—despite everyone’s best efforts—mistakes happen and will continue to happen, even when people’s lives are at stake. In medical diagnostics for example, roughly 200,000 patients die from preventable medical errors each year (James, 2013 ), and 5% of autopsies reveal lethal diagnostic errors that could have been averted (Shojania, Burton, McDonald, & Goldman, 2003 ). One of the main conclusions of an authoritative report on these errors by the National Institute of Medicine was that these mistakes do not result from individual recklessness or the actions of a particular group. Instead, it is important to design resilient systems that identify and enhance the positive capacities of people (Dekker, 2014 ). Rather than focusing on “bad apples” at the frontline, the report recommended the development of safeguards for people’s fallibility—to “make it harder for people to do something wrong and easier for them to do it right” (Institute of Medicine, 2000 , p. 2).

One such safeguard that has been highly successful across several domains has been to exploit the “collective intelligence” of groups who collaborate to solve problems well. The “wisdom of crowds” phenomenon dates back to Aristotle (see Landemore, 2012 ), it was later investigated by Galton ( 1907 ) and others more formally in the early 20th century (e.g., Gordon, 1924 ). The rise of “crowds” has since been promoted in a series of popular books (e.g., Surowiecki, 2004 ; Rheingold, 2007 ; McAfee & Brynjolfsson, 2017 ) and even in a short-lived crime television drama (Humphrey, 2017 ), and for good reason, since combining judgements from many individuals can be surprisingly accurate in prediction markets, forecasting sporting outcomes, box office success, and geopolitical and climate-related events (Escoffier & McKelvey, 2015 ; Hueffer, Fonseca, Leiserowitz, & Taylor, 2013 ; Tetlock, Mellers, Rohrbaugh, & Chen, 2014 ; Wolfers & Zitzewitz, 2004 ). The benefits of aggregation have also been identified across a range of safety-critical domains including the diagnosis of skin lesions (Kurvers, Krause, Argenziano, Zalaudek, & Wolf, 2015 ), the interpretation of mammograms (Wolf, Krause, Carney, Bogart, & Kurvers, 2015 ), diagnosis in emergency medicine (Kämmer, Hautz, Herzog, Kunina-Habenicht, & Kurvers, 2017 ), and matching unfamiliar faces (Balsdon, Summersby, Kemp, & White, 2018 ).

A useful analogy for thinking about system failures, such as medical mishaps or nuclear meltdowns, is the Swiss cheese model of errors by Reason ( 2000 ), which likens human systems to multiple slices of Swiss cheese layered on top of each other. Each defensive layer (e.g., alarms, physical barriers, automatic shutdowns) could prevent a breach from occurring, but has unintended flaws, or holes, which can all align and cause harm by allowing the hazard to pass through. One can think about the wisdom of crowds in a similar way: each rater is depicted as a slice of Swiss cheese; the fewer and smaller the holes, the more expertise one has, the less chance there is of making an error. As more people are layered on, if their decisions are independent and they approach the problem from different perspectives, then the holes will be misaligned, preventing the error from passing through. On the other hand, if the raters all have the same blind spots—where the “holes” align—then errors may slip through.

In this experiment, we extend this “wisdom of crowds” approach to fingerprint analysis by comparing the performance of individuals and crowds of professional fingerprint analysts. We test whether crowds of novice participants are as collectively wise as experts, and also evaluate the collective intelligence of the groups by comparing three different rules for aggregating people’s responses:

Follow-the-majority . Adopt the judgement with the most support in the group.

Follow-the-most-confident . Adopt the judgement with the highest confidence rating.

Follow-the-most-senior . Adopt the judgment of the most experienced examiner.

Majority and confidence rules have been used successfully in high-stakes domains such as breast and skin cancer detection (Kurvers et al., 2015 ), while the seniority rule is less common (Kämmer et al., 2017 ). Pooling the independent judgments of small groups of diagnosticians substantially increases performance relative to average individual performance, often better than the highest performing member. The best rule often depends on the size of the group, but in general, if the decisions being pooled are unbiased, diverse, and derived independently, then the collective output will typically outperform even the best member of the group (Surowiecki, 2004 ). All three of these decision rules are often used in practice across a range of applied contexts, but they can lead to very different outcomes. But what about fingerprint analysis? Is it more sensible to follow the majority, the most confident, or the most senior examiner?

The methods and materials for this experiment are available and described at length on the Open Science Framework, including our experiment code, video instructions, trial sequences, de-identified data, and analysis scripts ( http://tiny.cc/jbkxcz ).

Thirty-six professional fingerprint examiners from the Australian Federal Police, Queensland Police Service, Victoria Police, and New South Wales Police (13 females and 23 males, mean age = 46 years, SD = 8, mean experience = 16.4 years, SD = 8.6) volunteered their time. Thirty-six novice participants (25 females and 11 males, mean age = 21.6 years, SD = 3.6, with no formal experience with fingerprints) consisting of undergraduate psychology students who participated for course credit and members of the broader communities at The University of Queensland and The University of Adelaide also volunteered their time. A novice control group is important for establishing expertise (Thompson, Tangen, & McCarthy, 2013 ), and allows us to examine whether more domain knowledge makes for a wiser crowd—which may not always be the case (Herzog & Hertwig, 2011 ).

The “crime scene” prints and their matches were collected and developed at The University of Queensland from undergraduate students who left their prints on various surfaces (e.g., wood, plastic, metal, and glass), so unlike genuine crime-scene prints, they had a known true origin (Cole, 2005 ). Simulated prints were dusted by a research assistant (who was trained by a qualified fingerprint expert), photographed, cropped, and isolated in the frame. A qualified expert reported that each simulated print contained sufficient information to make an identification if there was a clear comparison exemplar.

Each of the 36 fingerprint examiners was presented with the same set of 24 fingerprint pairs from the same finger (targets) and 24 highly similar pairs from different fingers (distractors) in a different random order. Each pair consisted of a crime-scene “latent” fingerprint and a fully rolled “arrest” fingerprint, and participants were asked to provide a rating on a 12-point scale ranging from 1 (Sure Different) to 12 (Sure Same). On target trials, when the prints were from the same person, ratings from 7 to 12 count as a “true positive”; on distractor trials, when the prints were from different people, ratings from 7 to 12 count as a “false positive.” The distractors were created by running each latent fingerprint through the National Australian Fingerprint Identification System—which consists of roughly 67 million fingerprints—to return the most similar exemplars from the database (see Tangen et al., 2011 , for a similar methodology). On the first 44 of 48 trials (22 targets, 22 distractors), participants were given 20 s to examine the prints. On the final four trials (two targets, two distractors), they had an unlimited amount of time to make a decision. These four untimed trials were cycled across each of the fingerprint pairs across the 36 participants so that each fingerprint pair was examined by three different participants. After running these 36 fingerprint examiners through the experiment, we presented an identical set of 36 trial sequences with the same fingerprint pairs in the same order to 36 novice participants.

Individual Performance

The individual performance of the 36 novices (yellow) and 36 experts (purple) is illustrated in Fig.  1 . The true-positive rate (on the left) represents each person’s performance when the prints came from the same finger. “False negatives” on these target trials are the sort of mistakes that could potentially lead to false exonerations in practice. The false-positive rate (on the right) represents each person’s performance when the prints came from different fingers. “False positives” on these distractor trials are the sort of mistakes that could potentially lead to false convictions in practice. These results closely replicate previous findings (e.g., Tangen et al., 2011 ; Thompson, Tangen, & McCarthy, 2014 ) in which experts outperformed novices on distractor trials, and performed the same or slightly better than novices on target trials. This benefit of expertise is evident in Fig.  1 a during the 44 trials (22 targets, 22 distractors) in which participants were given 20 s to make a decision, and in Fig.  1 b during the four trials (two targets, two distractors) in which participants had no time limit on making a decision. In the 20-s condition with 44 trials, experts made true-positive decisions 71% (SD = 45%) of the time and false-positive decisions 8.5% (SD = 28%) of the time. Novices, by comparison, made true-positive decisions 71% (SD = 45%) of the time and false-positive decisions 50% (SD = 50%) of the time. In the untimed condition with four trials, experts made true-positive decisions 85% (SD = 36%) of the time and false positives 2.8% (SD = 17%) of the time. Novices, on the other hand, made true-positive decisions 76% (SD = 43%) of the time and false positives 60% (SD = 49%) of the time.

True- and false-positive rate for individual novices and experts after 20 s of analysis ( a ) or without a time limit ( b ). Each jittered data point represents the mean proportion of true or false positives for each individual participant. The red shape represents the mean and vertical bars ±1 standard deviation

A 2 (Group: novices vs. experts) × 2 (Rate Type: true vs. false positives) mixed ANOVA confirmed these impressions with significant main effects of Group, F (1, 70) = 61.34, p  < .001, η g 2  = .33, and Rate Type, F (1, 70) = 342.11, p  < .001, η g 2  = .68, along with a significant interaction, F (1, 70) = 84.25, p  < .001, η g 2  = .34 in the 20-s condition. The same pattern was evident in the unlimited condition: significant main effects of Group, F (1, 70) = 27.09, p  < .001, η g 2  = .16, and Rate Type, F (1, 35) = 110.62, p  < .001, η g 2  = .44, as well as a significant interaction, F (1, 70) = 48.47, p  < .001, η g 2  = .26.

Collective Performance

The most popular, transparent, and easiest method of aggregating people’s decisions is the majority rule (Hastie & Kameda, 2005 ). It is based on the commonsense notion that “many heads are better than one,” and is commonly used when making decisions in elections and committees: choose the option that gets more than half of the votes. In the experiment described above, each of the 48 pairs of fingerprints was either judged to be from “same” or “different” fingers by 36 professional fingerprint analysts and 36 novices. For each pair of prints, we took a random sample of three analysts, and tallied the decisions made by this trio using the majority rule. We then took another random group of three analysts, tallied their decisions, and repeated this process 2000 times and for groups of 3, 5, 7, and so on for each odd group size up to 35. The result was 2000 majority decisions for each of the 48 fingerprint pairs (24 targets and 24 distractors) across the 17 different group sizes. We repeated this process for novices as well.

The results of the simulation are illustrated in Fig.  2 . The individual true- and false-positive rates from Fig.  1 are represented as “Group Size, Number of Raters: 1” on the left side of each panel of Fig.  2 , respectively. As we aggregate the 20-s decisions of 3, 5, 7... experts moving along the x -axis of Fig.  2 a and c, the true-positive rate begins to increase and false-positive rate begins to decrease until they begin to level off at nine raters. For novices, however, their true-positive rate improves as more raters are included, but their false-positive rate remains at roughly 50% with a group of 35. When people are given an unlimited amount of time to decide—as illustrated in Fig.  2 b and d—the benefit of expertise is even more pronounced. The true-positive rate increases from 85% for individuals to 96% for groups of three experts, but increases from 76% for individual novices to 79% for novice trios. The false-positive rate is 2.8% for individual experts, and 0% for groups of three experts. The false-positive rate for novices is 60% for individuals, and 79% for groups of three novices.

Mean true-positive rates for groups of novices and experts after 20 s of analysis ( a ) or without a time limit ( b ), and mean false positive rates for groups of novices and experts after 20 s of analysis ( c ) or without a time limit ( d )

Pooling the independent judgements of a group of professional fingerprint analysts using a majority rule reduced their false-negative rate by up to 12% and their false-positive rate by up to 8%. Groups of novices, on the other hand, also received a boost in their true-positive rate of up to 19% with the majority rule, but their false-positive rate remained at roughly 50%.

Another way to represent these results is to combine people’s true- and false-positive rates into a single measure of discriminability, which calculates how well they can distinguish between prints from the same finger and prints from different fingers. We use a non-parametric model of discriminability that averages the minimum and maximum proper receiver operating characteristic curves through a point ( A ) for each individual expert and novice participant; an A value of .5 is chance and 1 is perfect discriminability (Zhang & Mueller, 2005 ). As illustrated by the dark purple data points in Fig.  3 , expert discrimination improves when taking the majority decision of small groups of examiners, leveling off at groups of nine, which is mirrored by a similar improvement by novices in dark yellow—just at a much lower level of performance.

Mean discriminability scores ( A ) for experts (purple) and novices (yellow) after 20 s of analysis ( a ) or without a time limit ( b ). The different shades of each color represent the three aggregation rules: (1) follow-the-majority; (2) follow-the-most-confident; and (3) follow-the-most-senior

The discriminability scores for the majority rule in Fig.  3 are presented alongside two other aggregation rules: (1) follow-the-most-confident and (2) follow-the-most-senior, which both improved the collective diagnostic performance of medical students (Kämmer et al., 2017 ).

We measured people’s absolute confidence on each trial by first collapsing across same and different on our 12-point scale, which ranged from 1 (Sure Different) to 12 (Sure Same), so each rating ranged from 1 (Unsure) to 6 (Sure). We then adopted the judgment with the highest confidence rating. For example, a random group of five people might provide ratings of 7, 10, 9, 8, and 1, which equates to confidence ratings of 1, 4, 3, 2, and 6. Even though four of the five provide a “Same” judgement, the extreme “Different” rating of 1 is the most extreme, so this highly confident examiner’s decision would be adopted. If people were equally confident about the two options, one was selected at random.

At the beginning of the experiment, each participant was asked to indicate how many years of formal experience they have with fingerprints. Given the follow-the-most-senior rule, we adopted the judgment of the most “senior” examiner in the crowd (i.e., the person with the greatest number of years examining prints). For example, a random group of five examiners might have 7, 10, 9, 18, and 25 years of experience. Even though the four less-experienced examiners each provide a “Same” judgement, since the most experienced examiner with 25 years of experience said, “Different,” this decision would be adopted. If examiners have the same level of experience, the response by one examiner was selected at random. Since none of the novice control participants had any experience with fingerprints, this rule was not applied to their ratings.

The output of these three aggregation rules is depicted in Fig.  3 . All three rules boosted collective performance compared to individual judgements—particularly in the unlimited time condition. For novices, the majority rule produced the largest increase when given 20 s to decide, and the confidence rule produced the largest gains in the unlimited condition. But even the output of the best aggregation rule applied to novice ratings paled in comparison to experts. The majority rule produced the largest collective performance boost for experts followed by the confidence rule followed by the seniority rule—both in the 20 s and unlimited time conditions.

Managing errors when lives and livelihoods are at stake requires resilient systems with safeguards that can tolerate mistakes and withstand their damaging effects (Reason, 2000 ). The wisdom of crowds may provide one such countermeasure to mitigate their impact, which motivated us to explore the role of collective intelligence in fingerprint analysis. Our results showed that individual experts performed exceedingly well, but they still made errors. Yet when we combined their decisions using a simple majority rule, these mistakes disappeared almost entirely. Pooling the decisions from small crowds of professional fingerprint analysts makes this wise group even wiser. Pooling the decisions from small crowds of novices, however, improved their true-positive rate, but at the cost of many more false positives. We tested the effect of two other aggregation methods. The first is to adopt the decision of the most confident person in the crowd and the second is to adopt the decision of the most experienced person in the crowd. Both of these pooling methods produced a slight improvement for experts compared to individual judgements depending on the condition, but the majority rule—which is the most common, transparent, and easiest method to adopt—delivered the most considerable boost in performance.

Our results add to the growing body of evidence that combining independent judgements can greatly improve the quality of decision-making in high-stakes domains. What makes this collective intelligence approach particularly appealing in these contexts is the robustness or “fault tolerance” that is built into the aggregation process. Instead of a single examiner bearing the weight of this important decision, the burden is distributed equally across several individuals. This redundancy provides some assurance that the system will not collapse with a single mistake. Such a system would be straightforward to implement; it embodies a team-based approach to decision-making, and would bring greater peace of mind to analysts, managers, and their organizations. Of course, it is also possible that examiners could feel less responsibility for their collective decisions compared to acting alone, so they may be less conservative or careful than usual if they assume other examiners will catch their mistakes (El Zein, Bahrami, & Hertwig, 2019 ). Despite the promise of a collective intelligence system, courts would need to figure out how to accommodate cases where decision-making is distributed (Kemp, White, & Edmond, in press ). Time and resourcing limitations could also be a consideration in adopting a distributed system, but each expert may not need to replicate the entire analysis that is currently performed by an individual examiner (Ballantyne, Edmond, & Found, 2017 ). Indeed, this experiment was conducted in a tightly controlled setting and should be replicated under typical conditions using actual casework materials, software tools, and timeframes. Assuming that our results generalize to everyday practice, pooling the decisions of crowds of expert analysts may provide an effective safeguard against miscarriages of justice.

Availability of data and materials

The data and code for each individual novice and expert participant used to produce our results and plots are available, with the exception of participants’ years of experience, which have been rank-ordered to preserve the identities of our participants.

Change history

29 september 2023.

A Correction to this paper has been published: https://doi.org/10.1186/s41235-023-00514-w

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Acknowledgements

We thank the Australian fingerprint examiners who participated in our research for giving their time and expertise so generously. We thank Amy Cramb and Molly Arendt for their assistance in collecting the data.

This research was supported by grant No. LP170100086 from the Australian Research Council to Tangen and Searston.

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Jason M. Tangen & Kirsty M. Kent

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In line with the CRediT taxonomy, JMT contributed to all aspects of the project: conceptualization, data curation, formal analysis, funding acquisition, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing, and editing. KMK contributed to the conceptualization, investigation, methodology, project administration, validation, writing, and editing. RAS contributed to the data curation, formal analysis, funding acquisition, investigation, project administration, resources, software, supervision, validation, visualization, writing, and editing. The authors read and approved the final manuscript.

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Correspondence to Jason M. Tangen .

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The reported studies were cleared in accordance with the ethical review processes of The University of Queensland and The University of Adelaide and are within the guidelines of the National Statement on Ethical Conduct in Human Research.

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Tangen, J.M., Kent, K.M. & Searston, R.A. Collective intelligence in fingerprint analysis. Cogn. Research 5 , 23 (2020). https://doi.org/10.1186/s41235-020-00223-8

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• Collective intelligence
• Wisdom of crowds
• Fingerprints
• Forensic science

Methodologies Applied to Fingerprint Analysis

Affiliations.

• 1 Department of Pharmacy, Federal University of Rio Grande do Sul, 2752 Ipiranga Ave, Lab 605A - Santana, Porto Alegre, 90610-000, RS, Brazil.
• 2 Identification Group, Brazilian Federal Police, Porto Alegre, 90610-093, RS, Brazil.
• 3 National Institute of Forensic Science and Technology - INCT FORENSE, 2752 Ipiranga Ave, Lab 605A - Santana, Porto Alegre, 90610-000, RS, Brazil.
• PMID: 32176818
• DOI: 10.1111/1556-4029.14313

This systematic review deals with the last 10 years of research in analytical methodologies for the analysis of fingerprints, regarding their chemical and biological constituents. A total of 123 manuscripts, which fit the search criteria defined using the descriptor "latent fingermarks analysis," were selected. Its main instrumental areas (mass spectrometry, spectroscopy, and innovative methods) were analyzed and summarized in a specific table, highlighting its main analytical parameters. The results show that most studies in this field use mass spectrometry to identify the constituents of fingerprints, both to determine the chemical profile and for aging. There is also a marked use of mass spectrometry coupled with chromatographic methods, and it provides accurate results for a fatty acid profile. Additional significant results are achieved by spectroscopic methods, mainly Raman and infrared. It is noteworthy that spectroscopic methods using microscopy assist in the accuracy of the analyzed region of the fingerprint, contributing to more robust results. There was also a significant increase in studies using methods focused on finding new developers or identifying components present in fingerprints by rapid tests. This systematic review of analytical techniques applied to the detection of fingerprints explores different approaches to contribute to future studies in forensic identification, verifying new demands in the forensic sciences and assisting in the selection of studies for the progress of research.

Keywords: forensic identification; forensic science; latent fingermarks; latent fingerprints; mass spectrometry; nanoparticles; spectroscopy.

© 2020 American Academy of Forensic Sciences.

Publication types

• Systematic Review
• Chromatography
• Dermatoglyphics*
• Fatty Acids / chemistry
• Forensic Sciences / methods*
• Immunoassay
• Lipids / chemistry
• Mass Spectrometry
• Nanoparticles
• Spectrum Analysis
• Time Factors
• Fatty Acids

Grants and funding

• 17/2551-0000839-1/Fundo de Amparo a Pesquisa do Rio Grande do sul - FAPERGS
• 16/2014/Conselho Nacional de Desenvolvimento Científico e Tecnológico
• 16/2014/National Institute of Forensic Science and Technology - INCT FORENSE
• 88882.345923/2019-01/Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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Criminal Justice

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Fingerprint analysis and databases.

This article delves into the critical role of fingerprint analysis and databases within the United States criminal justice process . Beginning with an exploration of the historical evolution of fingerprint analysis, the article elucidates the unique and permanent nature of fingerprints, encompassing diverse patterns and key identification features. It further examines traditional and modern techniques employed in fingerprint analysis, including ink and paper methods and advanced Automated Fingerprint Identification Systems (AFIS). Legal and ethical considerations surrounding the admissibility of fingerprint evidence in court are discussed, emphasizing the necessity of ensuring reliability and accuracy. Transitioning to fingerprint databases, the article provides an in-depth overview of national and state-level systems, detailing their implementation, integration with forensic databases, and the associated challenges. Real-world examples illustrate the substantial impact of fingerprint analysis on criminal investigations , emphasizing collaboration with other forensic methods. The article concludes by highlighting emerging trends and future advancements in the field, urging sustained research and development for continuous improvement. This comprehensive exploration aims to enhance understanding and awareness of the pivotal role fingerprints play in modern criminal justice.

Introduction

Fingerprint analysis stands as an indispensable pillar within the realm of criminal investigations, playing a pivotal role in identifying and linking individuals to criminal activities. The uniqueness and permanence of fingerprints make them a reliable biometric identifier, contributing significantly to the establishment of individual identity. This section will provide a brief overview of the profound significance that fingerprint analysis holds in aiding law enforcement agencies in solving crimes and bringing perpetrators to justice.

Tracing its roots back to the early 20th century, the historical evolution of fingerprint analysis is a fascinating journey marked by advancements in forensic science. From the pioneering work of Sir Francis Galton to the establishment of fingerprinting as a standard forensic practice, this subsection will illuminate the key milestones that have shaped fingerprint analysis into the sophisticated discipline it is today. Understanding the historical context is crucial for appreciating the continuous refinement and integration of fingerprint analysis within the broader framework of the criminal justice system.

Fingerprint databases serve as repositories of invaluable forensic information, transcending geographical boundaries and facilitating seamless collaboration among law enforcement agencies. This subsection will elucidate the purpose and role of fingerprint databases in enhancing criminal investigations. By detailing how these databases compile, store, and match fingerprint data, we will explore their instrumental role in expediting the identification process and connecting disparate criminal cases.

In summary, this article aims to provide a comprehensive exploration of fingerprint analysis and databases within the context of the US criminal justice process. By examining the historical evolution of fingerprint analysis, detailing the techniques involved, scrutinizing the legal and ethical considerations, delving into the intricacies of fingerprint databases, and assessing their impact on criminal investigations, this discussion seeks to offer a thorough understanding of the multifaceted role fingerprints play in modern forensic science.

Fingerprint Analysis

At the core of fingerprint analysis lies the fundamental principle that each individual possesses a unique and unalterable fingerprint pattern. This subsection will delve into the intricacies of why fingerprints are considered an exceptional biometric identifier, exploring the scientific basis behind their permanence and distinctiveness.

Fingerprint patterns manifest in distinct configurations, commonly classified as loops, arches, and whorls. This section will elucidate the significance of each pattern type, discussing their prevalence in the general population and the forensic importance of identifying and classifying these patterns in the investigative process.

Beyond overall patterns, the identification of specific ridge patterns and minutiae points forms the basis of individual fingerprint recognition. This subsection will explore the microscopic details critical to fingerprint identification, emphasizing the role of ridge patterns and minutiae points in forensic analysis.

Fingerprinting has evolved from traditional ink and paper methods, wherein individuals leave their impressions on paper through ink. This section will discuss the historical roots of this technique and its continued relevance in certain forensic contexts.

The advent of technology has revolutionized fingerprint analysis, with Automated Fingerprint Identification Systems (AFIS) taking center stage. This subsection will explore the technological advancements in AFIS, highlighting their efficiency in processing and matching fingerprints within vast databases.

Despite technological advancements, the expertise of forensic analysts remains crucial in fingerprint analysis. This section will elucidate the role of forensic experts in examining, comparing, and verifying fingerprint evidence, emphasizing the human element in ensuring accuracy and reliability.

Fingerprint evidence’s admissibility in court is a critical legal consideration. This subsection will explore the standards and criteria for admitting fingerprint evidence, addressing the foundational reliability required for its acceptance in legal proceedings.

Fingerprint analysis is not without challenges and controversies. This section will examine issues such as the potential for human error, the limitations of technology, and debates surrounding the infallibility of fingerprint evidence in criminal investigations.

Maintaining the reliability and accuracy of fingerprint examinations is paramount. This subsection will discuss quality assurance measures, standardization efforts, and ongoing research aimed at continually improving the precision of fingerprint analysis in forensic science.

Fingerprint Databases

Fingerprint databases play a crucial role in the modernization of criminal investigations. This section provides an insightful overview of both national and state-level fingerprint databases in the United States. It explores the establishment, purpose, and jurisdictional scope of these databases, emphasizing their collective contribution to enhancing law enforcement capabilities.

The effectiveness of fingerprint databases is contingent upon seamless coordination and collaboration among various law enforcement agencies. This subsection examines the intricate network of information sharing, protocols, and collaborative efforts that underpin the successful operation of fingerprint databases at different levels of governance.

The implementation of fingerprint databases involves systematic processes for the collection and storage of fingerprint data. This section delves into the methods employed by law enforcement agencies to collect and input fingerprint information into databases, emphasizing the standardization of data entry practices to ensure accuracy and reliability.

Fingerprint databases do not operate in isolation; they are integral components of broader forensic ecosystems. This subsection explores the integration of fingerprint databases with other forensic databases and information systems, illustrating how this integration enhances the overall efficacy of criminal investigations.

Real-world examples serve to underscore the impact of fingerprint databases in solving crimes. Through compelling case studies, this section illuminates instances where fingerprint databases have played a pivotal role in identifying perpetrators, connecting criminal activities, and expediting investigations, thereby showcasing their practical effectiveness.

As with any large-scale data repository, fingerprint databases are not immune to privacy concerns and legal limitations. This subsection addresses the ethical considerations surrounding the collection and utilization of fingerprint data, exploring legal frameworks and privacy safeguards designed to protect individual rights.

Fingerprint data is highly sensitive and must be safeguarded against unauthorized access and potential breaches. This section discusses the security measures implemented to protect the integrity of fingerprint data, including encryption protocols, access controls, and ongoing advancements in cybersecurity within the context of fingerprint databases.

Fingerprint databases often involve the collaboration of multiple law enforcement agencies. This subsection investigates the challenges and strategies associated with interagency cooperation, emphasizing the importance of standardization in database practices to ensure consistency and interoperability across jurisdictions. It also explores ongoing efforts to establish common protocols and standards within the field of fingerprint database management.

Impact on Criminal Investigations

Fingerprint analysis has been instrumental in solving a myriad of criminal cases. This section delves into compelling real-world examples where fingerprint evidence played a decisive role in identifying perpetrators and establishing crucial links in investigations. These case studies serve as powerful illustrations of the practical application and impact of fingerprint analysis in criminal justice.

Beyond individual case anecdotes, statistical data provides a quantitative perspective on the success rate of fingerprint analysis. This subsection explores relevant statistics, highlighting the reliability and efficacy of fingerprint analysis in contributing to successful case resolutions. Examining success rates across various types of crimes and demographics enhances our understanding of the broader impact.

Fingerprint analysis is often complemented by other forensic methods, most notably DNA analysis. This section explores collaborative efforts between fingerprint analysis and DNA analysis, showcasing how the integration of these techniques has led to more robust and conclusive evidence in criminal investigations. The synergy between fingerprint and DNA analysis enhances the overall accuracy and reliability of forensic findings.

Fingerprint analysis serves as a cornerstone within the comprehensive forensic toolkit employed by law enforcement agencies. This subsection examines how the integration of fingerprint analysis with other forensic techniques, such as ballistics and digital forensics, contributes to a holistic investigative approach. The combined use of multiple forensic disciplines strengthens law enforcement’s ability to reconstruct events, identify perpetrators, and build compelling cases for prosecution.

Technological advancements continually shape the landscape of fingerprint analysis. This section explores emerging technologies, such as 3D fingerprinting and advanced imaging techniques, and their potential impact on the precision and efficiency of fingerprint analysis. Understanding these innovations provides insights into the evolving capabilities of forensic experts.

Ongoing research and development initiatives play a pivotal role in advancing fingerprint analysis capabilities. This subsection delves into current R&D efforts aimed at enhancing the accuracy, speed, and scope of fingerprint analysis. It highlights collaborative projects between academia, industry, and law enforcement that contribute to the continuous improvement of fingerprint analysis methodologies and technologies.

In conclusion, the multifaceted impact of fingerprint analysis on criminal investigations is evident through its historical successes, statistical validation, and integration with other forensic methods. As technology evolves and research progresses, the future promises further enhancements in the capabilities of fingerprint analysis, solidifying its position as an indispensable tool in the pursuit of justice.

Fingerprint analysis stands as a cornerstone in the criminal justice process, embodying a rich history of forensic science evolution and contributing immeasurably to the resolution of criminal cases. The uniqueness and permanence of fingerprints make them unparalleled biometric identifiers, enabling law enforcement agencies to establish individual identities with a high degree of certainty. This section reiterates the profound significance of fingerprint analysis in criminal investigations, emphasizing its role in not only identifying suspects but also connecting individuals to crime scenes and fostering the overall integrity of the justice system.

The preceding sections of this article have provided a comprehensive examination of fingerprint analysis and databases within the context of the US criminal justice process. Beginning with an exploration of the historical evolution of fingerprint analysis, we delved into the intricate details of fingerprint patterns, minutiae points, and the methods employed in fingerprint analysis. Subsequently, the discussion expanded to cover the establishment and functioning of fingerprint databases, their integration with forensic ecosystems, and the challenges associated with managing such vast repositories of sensitive data. The article also highlighted the substantial impact of fingerprint analysis on criminal investigations, showcasing real-world examples, statistical data, and the collaborative efforts with other forensic methods. Lastly, the future of fingerprint analysis was explored, encompassing emerging technologies and ongoing research initiatives aimed at enhancing its capabilities.

While fingerprint analysis has proven to be an invaluable tool in the criminal justice process, there remains a call to action for continued research and improvement. Technological advancements, such as artificial intelligence and machine learning, offer new frontiers for enhancing the accuracy and efficiency of fingerprint analysis. This subsection advocates for sustained investment in research and development initiatives that focus on refining fingerprint analysis techniques and strengthening the security and interoperability of fingerprint databases. Moreover, the article encourages collaboration among academia, industry, and law enforcement agencies to foster innovation, share best practices, and address the evolving challenges in the realm of fingerprint forensics. By actively engaging in continuous improvement, the criminal justice system can ensure that fingerprint analysis remains a reliable and cutting-edge tool for years to come.

In conclusion, fingerprint analysis represents both a testament to the advancements in forensic science and an ongoing frontier for innovation. As we navigate the complexities of modern criminal investigations, the significance of fingerprints endures, and their analysis remains an indispensable element in the pursuit of justice. Through commitment to research, collaboration, and technological progress, the criminal justice community can further elevate the capabilities of fingerprint analysis, fortifying its role as a linchpin in the relentless pursuit of truth and accountability.

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Family-Based Fingerprint Analysis: A Position Paper

• First Online: 07 September 2022

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• Carlos Diego N. Damasceno   ORCID: orcid.org/0000-0001-8492-7484 10 &
• Daniel Strüber   ORCID: orcid.org/0000-0002-5969-3521 10 , 11  

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Thousands of vulnerabilities are reported on a monthly basis to security repositories, such as the National Vulnerability Database. Among these vulnerabilities, software misconfiguration is one of the top 10 security risks for web applications. With this large influx of vulnerability reports, software fingerprinting has become a highly desired capability to discover distinctive and efficient signatures and recognize reportedly vulnerable software implementations. Due to the exponential worst-case complexity of fingerprint matching, designing more efficient methods for fingerprinting becomes highly desirable, especially for variability-intensive systems where optional features add another exponential factor to its analysis. This position paper presents our vision of a framework that lifts model learning and family-based analysis principles to software fingerprinting. In this framework, we propose unifying databases of signatures into a featured finite state machine and using presence conditions to specify whether and in which circumstances a given input-output trace is observed. We believe feature-based signatures can aid performance improvements by reducing the size of fingerprints under analysis.

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In fact, we would like to thank for this well-crafted introduction that sparked our interest to the topic and led to the initial ideas of the first author’s doctoral thesis.

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Damasceno, C.D.N., Strüber, D. (2022). Family-Based Fingerprint Analysis: A Position Paper. In: Jansen, N., Stoelinga, M., van den Bos, P. (eds) A Journey from Process Algebra via Timed Automata to Model Learning . Lecture Notes in Computer Science, vol 13560. Springer, Cham. https://doi.org/10.1007/978-3-031-15629-8_8

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Advance in forensic fingerprint research provides new hope for cold cases

by Meg Cox, Loughborough University

Researchers have unveiled a method capable of detecting drug substances from fingerprints lifted from crime scenes, which could provide fresh insights into unsolved cases. The research is published in the journal Drug Testing and Analysis .

Analytical scientists from Loughborough University have demonstrated for the first time that drug residue—namely the fast-acting sleeping pill Zolpidem, which has been linked to drug-facilitated sexual assault and drink spiking —can be detected on gel-lifted fingerprints.

Dr. Jim Reynolds and Dr. Ayoung Kim say the breakthrough could shed new light on cold cases and unsolved crimes as forensic gel lifters—which transfer prints onto a gelatin surface—are used globally by scenes of crimes officers to preserve and visualize fingerprints.

"This is the first time that analysis of gel-lifted prints for a drug substance has been accomplished, and shows that lifted prints and other forensic marks can be interrogated for useful information," says Dr. Reynolds, the research lead.

"Since gel-lifted prints and marks can be stored for many years, the technique could be of real use in cold cases where additional information may prove useful to either link or exonerate a suspect to the investigation. Working with police forces and applying the method to cold case samples could help bring criminals to justice who may have thought they have got away with it."

A number of tests exist to detect drugs directly from fingerprints, but these face limitations. They can be destructive to the fingerprint, degrade drug residues, and be affected by environmental interferences.

It has long been speculated that gel-lifted prints contain valuable chemical information and could offer more accurate drug detection.

However, traditional techniques used to analyze the chemicals present in a sample have previously not been suitable for gel lifters. This is because they detect all chemicals present, including those that make up the gel, making it difficult to identify specific substances.

The method used by Dr. Reynolds and Dr. Kim, called sfPESI-MS, overcomes this issue using a rapid separation mechanism that distinguishes the drug substance from the background of the gel.

The process involves sampling the chemicals from the gel lifters into tiny liquid droplets. The chemicals extracted into the droplets are then ionized, which means they gain or lose electric charge depending on their chemical properties. The drug substance chemicals are more surface active than the chemicals originating from the gel, which enables them to be separated from the mixture.

This separation method enables the direct detection of a drug substance using mass spectrometry , a technique that identifies chemicals by measuring their molecular weight. The researchers have successfully tested the technique using Zolpidem-laced fingerprints lifted from glass, metal, and paper surfaces in a laboratory setting.

They now hope to work with police forces to analyze stored gel-lifted prints and use the method to identify other substances.

Dr. Reynolds said, "Zolpidem was the focus of our research, but the method could just as easily be applied to other drug substances a person may have been handling and could be applied to other chemicals such as explosives, gunshot residues, paints, and dyes.

"By linking chemical information to the fingerprint, we can identify the individual and link to the handling of an illicit substance which may prove useful in a prosecution. This could be useful to detect individuals who have been spiking drinks; for example, if the drug they are using gets onto their fingertips, then they will leave evidence at the scene."

Dr. Kim, who is the first author of the paper and completed the research as part of her Ph.D. at Loughborough, added, "We would like to apply our method to real samples from criminal investigations; it would be good to know my Ph.D. research has helped bring criminals to justice."

Journal information: Drug Testing and Analysis

Provided by Loughborough University

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DNA fingerprinting in forensics: past, present, future

Lutz roewer.

1 Department of Forensic Genetics, Institute of Legal Medicine and Forensic Sciences, Charité - Universitätsmedizin Berlin, Berlin, Germany

DNA fingerprinting, one of the great discoveries of the late 20th century, has revolutionized forensic investigations. This review briefly recapitulates 30 years of progress in forensic DNA analysis which helps to convict criminals, exonerate the wrongly accused, and identify victims of crime, disasters, and war. Current standard methods based on short tandem repeats (STRs) as well as lineage markers (Y chromosome, mitochondrial DNA) are covered and applications are illustrated by casework examples. Benefits and risks of expanding forensic DNA databases are discussed and we ask what the future holds for forensic DNA fingerprinting.

The past - a new method that changed the forensic world

'“I’ve found it! I’ve found it”, he shouted, running towards us with a test-tube in his hand. “I have found a re-agent which is precipitated by hemoglobin, and by nothing else”,’ says Sherlock Holmes to Watson in Arthur Conan Doyle’s first novel A study in Scarlet from1886 and later: 'Now we have the Sherlock Holmes’ test, and there will no longer be any difficulty […]. Had this test been invented, there are hundreds of men now walking the earth who would long ago have paid the penalty of their crimes’ [ 1 ].

The Eureka shout shook England again and was heard around the world when roughly 100 years later Alec Jeffreys at the University of Leicester, in UK, found extraordinarily variable and heritable patterns from repetitive DNA analyzed with multi-locus probes. Not being Holmes he refrained to call the method after himself but 'DNA fingerprinting’ [ 2 ]. Under this name his invention opened up a new area of science. The technique proved applicable in many biological disciplines, namely in diversity and conservation studies among species, and in clinical and anthropological studies. But the true political and social dimension of genetic fingerprinting became apparent far beyond academic circles when the first applications in civil and criminal cases were published. Forensic genetic fingerprinting can be defined as the comparison of the DNA in a person’s nucleated cells with that identified in biological matter found at the scene of a crime or with the DNA of another person for the purpose of identification or exclusion. The application of these techniques introduces new factual evidence to criminal investigations and court cases. However, the first case (March 1985) was not strictly a forensic case but one of immigration [ 3 ]. The first application of DNA fingerprinting saved a young boy from deportation and the method thus captured the public’s sympathy. In Alec Jeffreys’ words: 'If our first case had been forensic I believe it would have been challenged and the process may well have been damaged in the courts’ [ 4 ]. The forensic implications of genetic fingerprinting were nevertheless obvious, and improvements of the laboratory process led already in 1987 to the very first application in a forensic case. Two teenage girls had been raped and murdered on different occasions in nearby English villages, one in 1983, and the other in 1986. Semen was obtained from each of the two crime scenes. The case was spectacular because it surprisingly excluded a suspected man, Richard Buckland, and matched another man, Colin Pitchfork, who attempted to evade the DNA dragnet by persuading a friend to give a sample on his behalf. Pitchfork confessed to committing the crimes after he was confronted with the evidence that his DNA profile matched the trace DNA from the two crime scenes. For 2 years the Lister Institute of Leicester where Jeffreys was employed was the only laboratory in the world doing this work. But it was around 1987 when companies such as Cellmark, the academic medico-legal institutions around the world, the national police, law enforcement agencies, and so on started to evaluate, improve upon, and employ the new tool. The years after the discovery of DNA fingerprinting were characterized by a mood of cooperation and interdisciplinary research. None of the many young researchers who has been there will ever forget the DNA fingerprint congresses which were held on five continents, in Bern (1990), in Belo Horizonte (1992), in Hyderabad (1994), in Melbourne (1996), and in Pt. Elizabeth (1999), and then shut down with the good feeling that the job was done. Everyone read the Fingerprint News distributed for free by the University of Cambridge since 1989 (Figure  1 ). This affectionate little periodical published non-stylish short articles directly from the bench without impact factors and resumed networking activities in the different fields of applications. The period in the 1990s was the golden research age of DNA fingerprinting succeeded by two decades of engineering, implementation, and high-throughput application. From the Foreword of Alec Jeffreys in Fingerprint News , Issue 1, January 1989: 'Dear Colleagues, […] I hope that Fingerprint News will cover all aspects of hypervariable DNA and its application, including both multi-locus and single-locus systems, new methods for studying DNA polymorphisms, the population genetics of variable loci and the statistical analysis of fingerprint data, as well as providing useful technical tips for getting good DNA profiles […]. May your bands be variable’ [ 5 ].

Cover of one of the first issues of Fingerprint News from 1990.

Jeffreys’ original technology, now obsolete for forensic use, underwent important developments in terms of the basic methodology, that is, from Southern blot to PCR, from radioactive to fluorescent labels, from slab gels to capillary electrophoresis. As the technique became more sensitive, the handling simple and automated and the statistical treatment straightforward, DNA profiling, as the method was renamed, entered the forensic routine laboratories around the world in storm. But, what counts in the Pitchfork case and what still counts today is the process to get DNA identification results accepted in legal proceedings. Spectacular fallacies, from the historical 1989 case of People vs. Castro in New York [ 6 ] to the case against Knox and Sollecito in Italy (2007–2013) where literally DNA fingerprinting was on trial [ 7 ], disclosed severe insufficiencies in the technical protocols and especially in the DNA evidence interpretation and raised nolens volens doubts on the scientific and evidentiary value of forensic DNA fingerprinting. These cases are rare but frequent enough to remind each new generation of forensic analysts, researchers, or private sector employees that DNA evidence is nowadays an important part of factual evidence and needs thus intense scrutiny for all parts of the DNA analysis and interpretation process.

In the following I will briefly describe the development of DNA fingerprinting to a standardized investigative method for court use which has since 1984 led to the conviction of thousands of criminals and to the exoneration of many wrongfully suspected or convicted individuals [ 8 ]. Genetic fingerprinting per se could of course not reduce the criminal rate in any of the many countries in the world, which employ this method. But DNA profiling adds hard scientific value to the evidence and strengthens thus (principally) the credibility of the legal system.

The technological evolution of forensic DNA profiling

In the classical DNA fingerprinting method radio-labeled DNA probes containing minisatellite [ 9 ] or oligonucleotide sequences [ 10 ] are hybridized to DNA that has been digested with a restriction enzyme, separated by agarose electrophoresis and immobilized on a membrane by Southern blotting or - in the case of the oligonucleotide probes - immobilized directly in the dried gel. The radio-labeled probe hybridizes to a set of minisatellites or oligonucleotide stretches in genomic DNA contained in restriction fragments whose size differ because of variation in the numbers of repeat units. After washing away excess probe the exposure to X-ray film (autoradiography) allows these variable fragments to be visualized, and their profiles compared between individuals. Minisatellite probes, called 33.6 and 33.15, were most widely used in the UK, most parts of Europe and the USA, whereas pentameric (CAC)/(GTG) 5 probes were predominantly applied in Germany. These so-called multilocus probes (MLP) detect sets of 15 to 20 variable fragments per individual ranging from 3.5 to 20 kb in size (Figure  2 ). But the multi-locus profiling method had several limitations despite its successful application to crime and kinship cases until the middle of the 1990s. Running conditions or DNA quality issues render the exact matching between bands often difficult. To overcome this, forensic laboratories adhered to binning approaches [ 11 ], where fixed or floating bins were defined relative to the observed DNA fragment size, and adjusted to the resolving power of the detection system. Second, fragment association within one DNA fingerprint profile is not known, leading to statistical errors due to possible linkage between loci. Third, for obtaining optimal profiles the method required substantial amounts of high molecular weight DNA [ 12 ] and thus excludes the majority of crime-scene samples from the analysis. To overcome some of these limitations, single-locus profiling was developed [ 13 ]. Here a single hypervariable locus is detected by a specific single-locus probe (SLP) using high stringency hybridization. Typically, four SLPs were used in a reprobing approach, yielding eight alleles of four independent loci per individual. This method requires only 10 ng of genomic DNA [ 14 ] and has been validated through extensive experiments and forensic casework, and for many years provided a robust and valuable system for individual identification. Nevertheless, all these different restriction fragment length polymorphism (RFLP)-based methods were still limited by the available quality and quantity of the DNA and also hampered by difficulties to reliably compare genetic profiles from different sources, labs, and techniques. What was needed was a DNA code, which could ideally be generated even from a single nucleated cell and from highly degraded DNA, a code, which could be rapidly generated, numerically encrypted, automatically compared, and easily supported in court. Indeed, starting in the early 1990s DNA fingerprinting methods based on RFLP analysis were gradually supplanted by methods based on PCR because of the improved sensitivity, speed, and genotyping precision [ 15 ]. Microsatellites, in the forensic community usually referred to short tandem repeats (STRs), were found to be ideally suited for forensic applications. STR typing is more sensitive than single-locus RFLP methods, less prone to allelic dropout than VNTR (variable number of tandem repeat) systems [ 16 ], and more discriminating than other PCR-based typing methods, such as HLA-DQA1 [ 17 ]. More than 2,000 publications now detail the technology, hundreds of different population groups have been studied, new technologies as, for example, the miniSTRs [ 18 ] have been developed and standard protocols have been validated in laboratories worldwide (for an overview see [ 19 ]). Forensic DNA profiling is currently performed using a panel of multi-allelic STR markers which are structurally analogous to the original minisatellites but with much shorter repeat tracts and thus easier to amplify and multiplex with PCR. Up to 30 STRs can be detected in a single capillary electrophoresis injection generating for each individual a unique genetic code. Basically there are two sets of STR markers complying with the standards requested by criminal databases around the world: the European standard set of 12 STR markers [ 20 ] and the US CODIS standard of 13 markers [ 21 ]. Due to partial overlap, they form together a standard of 18 STR markers in total. The incorporation of these STR markers into commercial kits has improved the application of these markers for all kinds of DNA evidence with reproducible results from as less than three nucleated cells [ 22 ] and extracted even from severely compromised material. The probability that two individuals will have identical markers at each of 13 different STR loci within their DNA exceeds one out of a billion. If a DNA match occurs between an accused individual and a crime scene stain, the correct courtroom expression would be that the probability of a match if the crime-scene sample came from someone other than the suspect (considering the random, not closely-related man) is at most one in a billion [ 14 ]. The uniqueness of each person’s DNA (with the exception of monozygotic twins) and its simple numerical codification led to the establishment of government-controlled criminal investigation DNA databases in the developed nations around the world, the first in 1995 in the UK [ 23 ]. When a match is made from such a DNA database to link a crime scene sample to an offender who has provided a DNA sample to a database that link is often referred to as a cold hit. A cold hit is of value as an investigative lead for the police agency to a specific suspect. China (approximately 16 million profiles, the United States (approximately 10 million profiles), and the UK (approximately 6 million profiles) maintain the largest DNA database in the world. The percentage of databased persons is on the increase in all countries with a national DNA database, but the proportions are not the same by the far: whereas in the UK about 10% of the population is in the national DNA database, the percentage in Germany and the Netherlands is only about 0.9% and 0.8%, respectively [ 24 ].

Multilocus DNA Fingerprint from a large family probed with the oligonucleotide (GTG) 5 ( Courtesy of Peter Nürnberg, Cologne Center for Genomics, Germany ).

Lineage markers in forensic analysis

Lineage markers have special applications in forensic genetics. Y chromosome analysis is very helpful in cases where there is an excess of DNA from a female victim and only a low proportion from a male perpetrator. Typical examples include sexual assault without ejaculation, sexual assault by a vasectomized male, male DNA under the fingernails of a victim, male 'touch’ DNA on the skin, and the clothing or belongings of a female victim. Mitochondrial DNA (mtDNA) is of importance for the analyses of low level nuclear DNA samples, namely from unidentified (typically skeletonized) remains, hair shafts without roots, or very old specimens where only heavily degraded DNA is available [ 25 ]. The unusual non-recombinant mode of inheritance of Y and mtDNA weakens the statistical weight of a match between individual samples but makes the method efficient for the reconstruction of the paternal or maternal relationship, for example in mass disaster investigations [ 26 ] or in historical reconstructions. A classic case is the identification of two missing children of the Romanov family, the last Russian monarchy. MtDNA analysis combined with additional DNA testing of material from the mass grave near Yekaterinburg gave virtually irrefutable evidence that the two individuals recovered from a second grave nearby are the two missing children of the Romanov family: the Tsarevich Alexei and one of his sisters [ 27 ]. Interestingly, a point heteroplasmy, that is, the presence of two slightly different mtDNA haplotypes within an individual, was found in the mtDNA of the Tsar and his relatives, which was in 1991 a contentious finding (Figure  3 ). In the early 1990s when the bones were first analyzed, a point heteroplasmy was believed to be an extremely rare phenomenon and was not readily explainable. Today, the existence of heteroplasmy is understood to be relatively common and large population databases can be searched for its frequency at certain positions. The mtDNA evidence in the Romanov case was underpinned by Y-STR analysis where a 17-locus haplotype from the remains of Tsar Nicholas II matched exactly to the femur of the putative Tsarevich and also to a living Romanov relative. Other studies demonstrated that very distant family branches can be traced back to common ancestors who lived hundreds of years ago [ 28 ]. Currently forensic Y chromosome typing has gained wide acceptance with the introduction of highly sensitive panels of up to 27 STRs including rapidly mutating markers [ 29 ]. Figure  4 demonstrates the impressive gain of the discriminative power with increasing numbers of Y-STRs. The determination of the match probability between Y-STR or mtDNA profiles via the mostly applied counting method [ 30 ] requires large, representative, and quality-assessed databases of haplotypes sampled in appropriate reference populations, because the multiplication of individual allele frequencies is not valid as for independently inherited autosomal STRs [ 31 ]. Other estimators for the haplotype match probability than the count estimator have been proposed and evaluated using empirical data [ 32 ], however, the biostatistical interpretation remains complicated and controversial and research continues. The largest forensic Y chromosome haplotype database is the YHRD ( http://www.yhrd.org ) hosted at the Institute of Legal Medicine and Forensic Sciences in Berlin, Germany, with about 115,000 haplotypes sampled in 850 populations [ 33 ]. The largest forensic mtDNA database is EMPOP ( http://www.empop.org ) hosted at the Institute of Legal Medicine in Innsbruck, Austria, with about 33,000 haplotypes sampled in 63 countries [ 34 ]. More than 235 institutes have actually submitted data to the YHRD and 105 to EMPOP, a compelling demonstration of the level of networking activities between forensic science institutes around the world. That additional intelligence information is potentially derivable from such large datasets becomes obvious when a target DNA profile is searched against a collection of geographically annotated Y chromosomal or mtDNA profiles. Because linearly inherited markers have a highly non-random geographical distribution the target profile shares characteristic variants with geographical neighbors due to common ancestry [ 35 ]. This link between genetics, genealogy, and geography could provide investigative leads for investigators in non-suspect cases as illustrated in the following case [ 36 ]:

Screenshot of the 16169 C/T heteroplasmy present in Tsar Nicholas II using both forward and reverse sequencing primers ( Courtesy of Michael Coble, National Institute of Standards and Technology, Gaithersburg, USA ).

Correlation between the number of analyzed Y-STRs and the number of different haplotypes detected in a global population sample of 18,863 23-locus haplotypes.

In 2002, a woman was found with a smashed skull and covered in blood but still alive in her Berlin apartment. Her life was saved by intensive medical care. Later she told the police that she had let a man into her apartment, and he had immediately attacked her. The man was subletting the apartment next door. The evidence collected at the scene and in the neighboring apartment included a baseball cap, two towels, and a glass. The evidence was sent to the state police laboratory in Berlin, Germany and was analyzed with conventional autosomal STR profiling. Stains on the baseball cap and on one towel revealed a pattern consistent with that of the tenant, whereas two different male DNA profiles were found on a second bath towel and on the glass. The tenant was eliminated as a suspect because he was absent at the time of the offense, but two unknown men (different in autosomal but identical in Y-STRs) who shared the apartment were suspected. Unfortunately, the apartment had been used by many individuals of both European and African nationalities, so the initial search for the two men became very difficult. The police obtained a court order for Y-STR haplotyping to gain information about the unknown men’s population affiliation. Prerequisites for such biogeographic analyses are large reference databases containing Y-STR haplotypes also typed for ancestry informative single nucleotide markers (SNP) markers from hundreds of different populations. The YHRD proved useful to infer the population origin of the unknown man. The database inquiry indicated a patrilineage of Southern European ancestry, whereas an African descent was unlikely (Figure  5 ). The police were able to track down the tenant in Italy, and with his help, establish the identity of one of the unknown men, who was also Italian. When questioning this man, the police used the information retrieved from Y-STR profiling that he had shared the apartment in Berlin with a paternal relative. This relative was identified as his nephew. Because of the close-knit relationship within the family, this information would probably not have been easily retrieved from the uncle without the prior knowledge. The nephew was suspected of the attempted murder in Berlin. He was later arrested in Italy, where he had committed another violent robbery.

Screenshot from the YHRD depicting the radiation of a 9-locus haplotype belonging to haplogroup J in Southern Europe.

Information on the biogeographic origin of an unknown DNA could also be retrieved from a number of ancestry informative SNPs (AISNPs) on autosomes or insertion/deletion polymorphisms [ 37 , 38 ] but perhaps even better from so-called mini-haplotypes with only <10 SNPs spanning small molecular intervals (<10 kb) with very low recombination among sites [ 39 ]. Each 'minihap’ behaves like a locus with multiple haplotype lineages (alleles) that have evolved from the ancestral human haplotype. All copies of each distinct haplotype are essentially identical by descent. Thus, they fall like Y and mtDNA into the lineage-informative category of genetic markers and are thus useful for connecting an individual to a family or ancestral genetic pool.

Benefits and risks of forensic DNA databases

The steady growth in the size of forensic DNA databases raises issues on the criteria of inclusion and retention and doubts on the efficiency, commensurability, and infringement of privacy of such large personal data collections. In contrast to the past, not only serious but all crimes are subject to DNA analysis generating millions and millions of DNA profiles, many of which are stored and continuously searched in national DNA databases. And as always when big datasets are gathered new mining procedures based on correlation became feasible. For example, 'Familial DNA Database Searching’ is based on near matches between a crime stain and a databased person, which could be a near relative of the true perpetrator [ 40 ]. Again the first successful familial search was conducted in UK in 2004 and led to the conviction of Craig Harman of manslaughter. Craig Harman was convicted because of partial matches from Harman’s brother. The strategy was subsequently applied in some US states but is not conducted at the national level. It was during a dragnet that it first became public knowledge that the German police were also already involved in familial search strategies. In a little town in Northern Germany the police arrested a young man accused of rape because they had analyzed the DNA of his two brothers who had participated in the dragnet. Because of partial matches between crime scene DNA profiles and these brothers they had identified the suspect. In contrast to other countries, the Federal Constitutional Court of Germany decided in December 2012 against the future court use of this kind of evidence.

Civil rights and liberties are crucial for democratic societies and plans to extend forensic DNA databases to whole populations need to be condemned. Alec Jeffreys early on has questioned the way UK police collects DNA profiles, holding not only convicted individuals but also arrestees without conviction, suspects cleared in an investigation, or even innocent people never charged with an offence [ 41 ]. He also criticized that large national databases as the NDNAD of England and Wales are likely skewed socioeconomically. It has been pointed out that most of the matches refer to minor offences; according to GeneWatch in Germany 63% of the database matches provided are related to theft while <3% related to rape and murder. The changes to the UK database came in the 2012’s Protection of Freedoms bill, following a major defeat at the European Court of Human Rights in 2008. As of May 2013 1.1 million profiles (of about 7 million) had been destroyed to remove innocent people’s profiles from the database. In 2005 the incoming government of Portugal proposed a DNA database containing samples from every Portuguese citizen. Following public objections, the government limited the database to criminals. A recent study on the public views on DNA database-related matters showed that a more critical attitude towards wider national databases is correlated with the age and education of the respondents [ 42 ]. A deeper public awareness on the benefits and risks of very large DNA collections need to be built and common ethical and privacy standards for the development and governance of DNA databases need to be adopted where the citizen’s perspectives are taken into consideration.

The future of forensic DNA analysis

The forensic community, as it always has, is facing the question in which direction the DNA Fingerprint technology will be developed. A growing number of colleagues are convinced that DNA sequencing will soon replace methods based on fragment length analysis and there are good arguments for this position. With the emergence of current Next Generation Sequencing (NGS) technologies, the body of forensically useful data can potentially be expanded and analyzed quickly and cost-efficiently. Given the enormous number of potentially informative DNA loci - which of those should be sequenced? In my opinion there are four types of polymorphisms which deserve a place on the analytic device: an array of 20–30 autosomal STRs which complies with the standard sets used in the national and international databases around the world, a highly discriminating set of Y chromosomal markers, individual and signature polymorphisms in the control and coding region of the mitochondrial genome [ 43 ], as well as ancestry and phenotype inference SNPs [ 44 ]. Indeed, a promising NGS approach with the simultaneous analysis of 10 STRs, 386 autosomal ancestry and phenotype informative SNPs, and the complete mtDNA genome has been presented recently [ 45 ] (Figure  6 ). Currently, the rather high error rates are preventing NGS technologies from being used in forensic routine [ 46 ], but it is foreseeable that the technology will be improved in terms of accuracy and reliability. Time is another essential factor in police investigations which will be considerably reduced in future applications of DNA profiling. Commercial instruments capable of producing a database-compatible DNA profile within 2 hours exist [ 47 ] and are currently under validation for law enforcement use. The hands-free 'swab in - profile out’ process consists of automated extraction, amplification, separation, detection, and allele calling without human intervention. In the US the promise of on-site DNA analysis has already altered the way in which DNA could be collected in future. In a recent decision the Supreme court of the United States held that 'when officers make an arrest supported by probable cause to hold for a serious offense and bring the suspect to the station to be detained in custody, taking and analyzing a cheek swab of the arrestee’s DNA is, like fingerprinting and photographing, a legitimate police booking procedure’ (Maryland v. Alonzo Jay King, Jr.). In other words, DNA can be taken from any arrestee, rightly or wrongly arrested, as a part of the normal booking procedure. Twenty-eight states and the federal government now take DNA swabs after arrests with the aim of comparing profiles to the CODIS database, creating links to unsolved cases and to identify the person (Associated Press, 3 June 2013). Driven by the rapid technological progress DNA actually becomes another metric of quick identification. It remains to be seen whether rapid DNA technologies will alter the way in which DNA is collected by police in other countries. In Germany for example the DNA collection is still regulated by the code of the criminal procedure and the use of DNA profiling for identification purposes only is excluded. Because national legislations are basically so different, a worldwide system to interrogate DNA profiles from criminal justice databases seems currently a very distant project.

Schematic overview of Haloplex targeting and NGS analysis of a large number of markers simultaneously. Sequence data are shown for samples from two individuals and the D3S1358 STR marker, the rs1335873 SNP marker, and a part of the HVII region of mtDNA ( Courtesy of Marie Allen, Uppsala University, Sweden ).

At present the forensic DNA technology directly affects the lives of millions people worldwide. The general acceptance of this technique is still high, reports on the DNA identification of victims of the 9/11 terrorist attacks [ 48 ], of natural disasters as the Hurricane Katrina [ 49 ], and of recent wars (for example, in former Yugoslavia [ 50 ]) and dictatorship (for example, in Argentina [ 51 ]) impress the public in the same way as police investigators in white suits securing DNA evidence at a broken door. CSI watchers know, and even professionals believe, that DNA will inevitably solve the case just following the motto Do Not Ask, it’s DNA, stupid! But the affirmative view changes and critical questions are raised. It should not be assumed that the benefits of forensic DNA fingerprinting will necessarily override the social and ethical costs [ 52 ].

This short article leaves many of such questions unanswered. Alfred Nobel used his fortune to institute a prize for work 'in ideal direction’. What would be the ideal direction in which DNA fingerprinting, one of the great discoveries in recent history, should be developed?

Competing interests

The author declares that he has no competing interests.

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