Law Enforcement Investigations Research Articles

Innovative Learning in a Digital Forensics Laboratory: Tools and Techniques for Data Recovery

Electronic evidence is an essential component in most legal trials of criminal activities, and digital forensics is therefore a crucial support for law enforcement investigations. For instance, a wide range of electronic devices contain Not AND (NAND) flash memory chips, and when a criminal leaves digital evidence on non-operational or locked systems, accessing this memory is crucial. Student acquisition of the necessary competences and skills associated with electronic devices, their basic principles, and the associated technologies can be provided by experimental training, as done with the optional Digital Forensics module included in the degree in Criminalistics: Forensic Sciences and Technologies offered by the University of Alcalá (Spain). This module equips students with the appropriate skills to extract, process, and authenticate evidence information using suitable tools. The purpose of this study was to investigate the effectiveness of experimental learning, deployed through laboratory digital forensic tasks. A literature review was conducted of novel data extraction and analysis tools and procedures as a guide to the design of data recovery tasks incorporating experimental learning. Drawing on student feedback, our results highlight positive learning outcomes for the students. It is concluded that powerful forensic image analysis freeware is capable of identifying elements, and practical tests involving JTAG/chip−off extraction and analysis yield favorable results. A proposal for future studies is to reduce the destructiveness of invasive extraction methods.

The AI-shift: how Europol is leveraging artificial intelligence to combat serious organised crime and terrorism

Aim: The aim of this article is to highlight the importance of leveraging Artificial Intelligence (AI) in law enforcement to combat serious organised crime and terrorism, while ensuring responsible and accountable use of AI tools through collaboration and knowledge-sharing among European law enforcement agencies. Methodology: The study uses a descriptive methodology to describe the development and cooperation process through which the Innovation Lab contributes to the innovation development and knowledge sharing of Europol and its member countries. Findings: With the increasing volume and speed of investigative data, AI has emerged as a promising solution to help law enforcement agencies process and analyse large and complex datasets. Europol has been at the forefront of developing and sharing AI tools with its Member States, ensuring their responsible and accountable use. The integration of Artificial Intelligence (AI) in law enforcement investigations has been found to significantly enhance the efficiency and effectiveness of crime fighting, particularly in processing and analysing large and complex datasets. Value: The article highlights the importance of collaboration and knowledge-sharing among law enforcement agencies to keep pace with AI advancements and prevent criminal abuse of these technologies.

Az MI-fordulat: hogyan használja fel az Europol a mesterséges intelligenciát a súlyos szervezett bűnözés és a terrorizmus elleni küzdelemben

Aim: The aim of this article is to highlight the importance of leveraging Artificial Intelligence (AI) in law enforcement to combat serious organised crime and terrorism, while ensuring responsible and accountable use of AI tools through collaboration and knowledge-sharing among European law enforcement agencies. Methodology: The study uses a descriptive methodology to describe the development and cooperation process through which the Innovation Lab contributes to the innovation development and knowledge sharing of Europol and its member countries. Findings: With the increasing volume and speed of investigative data, AI has emerged as a promising solution to help law enforcement agencies process and analyse large and complex datasets. Europol has been at the forefront of developing and sharing AI tools with its Member States, ensuring their responsible and accountable use. The integration of Artificial Intelligence (AI) in law enforcement investigations has been found to significantly enhance the efficiency and effectiveness of crime fighting, particularly in processing and analysing large and complex datasets. Value: The article highlights the importance of collaboration and knowledge-sharing among law enforcement agencies to keep pace with AI advancements and prevent criminal abuse of these technologies.

Live Memory Forensic: Capture and Analyzing Volatile Data

As almost 90% of malware is resident in memory, live memory forensics is an essential part of cybersecurity. Live memory forensics refers to the process of analyzing computer RAM or volatile memory (which is lost after rebooting) while the computer is running. This article provides depth on live memory forensics, which is key in the detection and analysis of cyber threats and forensics investigations. Case studies and actual events demonstrate how this method can detect unauthorized access and discover hidden malware, which will help law enforcement investigators. The practical uses of Live Memory Forensics are illustrated using real world examples. Currently, live memory forensics are faced with the temporal nature of volatile data, other technical challenges, the instantiation of indirect data related to data privacy, and evidence handling problems. The paper emphasizes the importance of moral attitude and careful handling of data to keep the forensic process incorrupt. Investigators and cybersecurity professionals should now have a good understanding of live memory forensics and how to utilize live memory forensics to enhance security across borders, not just as a detective technique.

Dense SNP-based analyses complement forensic anthropology biogeographical ancestry assessments

Identification of unidentified human remains (UHRs) is crucial yet challenging, especially with traditional forensic techniques. Forensic anthropological examinations can yield ancestry estimations; however, the utility of these estimates is limited by the data points that can be collected from partial remains, complexities of admixture, and variation of phenotypic expression due to environmental effects. While it is generally known that anthropological estimates can be imprecise, the performance of these methods has not been studied at scale. Genome-wide SNP testing is an orthogonal approach for estimating ancestry and offers a unique opportunity to measure the magnitude of anthropological ancestry misattribution. Genomic ancestry inference leverages principal component analysis (PCA) and model-based clustering approaches. This study compares anthropologically determined ancestry with those estimated using genome-wide SNP markers. A dataset of 611 UHR samples with publicly available ancestry assessments from National Missing and Unidentified Persons System (NamUs) was analyzed. The genetic ancestry approach, validated against reference population samples, offers robust ancestry calculations for major population groups. Inconsistency between anthropological and genomic ancestry assignments were observed, particularly for admixed populations. Although forensic anthropological examinations remain valuable, their limitations emphasize the need for refinement and enhancement through the augmentation of SNP-based analyses. Further validation studies are crucial to define the uncertainty associated with both anthropological and genome-based ancestry estimates to resolve cases and aid law enforcement investigations. Additionally, current policy and practices for reporting ancestry for UHRs should be revisited to reduce potential misinformation.

Proposal of Legal Status of the Expert Valuation Institute Objectifying the Acquisition Process

The process of procuring military equipment, technology, material, and associated services (VM) is frequently shrouded in concerns about cost-effectiveness and, in some instances, even becomes the focus of law enforcement investigations. This often leads to delays in strategic investments and exposes involved individuals to the risk of criminal charges. Additionally, there is a notable lack of capacity to impartially evaluate the overall investment's efficacy. Consequently, the "Znalec" (Expert Witness) project was initiated as a part of the defense research program. Its objective is to explore the feasibility of establishing an expert institute that could impartially assess the value of the military procurements, set a standard for evaluating these assets, and outline a training program for relevant experts. This paper specifically addresses the first objective of the project, proposing a legal framework for the expert institute based on an extensive systems analysis.

Literature review about Forensic Toxicology and Poisoning

The field of toxicology is the research and investigation of the properties, processes fatalities, effective dosage, recognition, evaluation, and deductive reasoning of the results of toxicological tests, in addition to the handling of poisons. Forensic toxicology focuses on the therapeutic and juridical consequences of contaminants' harmful effects on people. If a material penetrates into the human body or comes into contact with any portion of it, regardless of whether it is solid, liquid, or gaseous, it is deemed toxic. The local the surroundings, the body's structure, or both may have an impact on poisoning. Because even compounds that seem safe in little quantities can become lethal when taken in large quantities, and because toxins generated through bacteria aren't typically regarded as toxic substances, the concept of poison comes with an imprecise and inappropriate definition. Based on a forensic perspective, it is crucial to understand that there are two approaches taken in the criminal investigation of the poisoning case. In the first case, it's crucial to ascertain the kind of damage caused and the poison's consequences; in the second, on the other hand, it's critical to locate the perpetrator and ascertain their reasons. Poisoning may sometimes result in death, but it can also have long-term health implications on the victim. This suggests that law enforcement investigations into contamination are a very complex procedure involving experts spanning multiple disciplines.

Raman Spectroscopy for the Time since Deposition Estimation of a Menstrual Bloodstain.

Forensic chemistry plays a crucial role in aiding law enforcement investigations by applying analytical techniques for the analysis of evidence. While bloodstains are frequently encountered at crime scenes, distinguishing between peripheral and menstrual bloodstains presents a challenge. This is due to their similar appearance post-drying. Raman spectroscopy has emerged as a promising technique capable of discriminating between the two types of bloodstains, offering invaluable probative information. Moreover, estimating the time since deposition (TSD) of bloodstains aids in crime scene reconstruction and prioritizing what evidence to collect. Despite extensive research focusing on TSD estimations, primarily in peripheral bloodstains, a crucial gap exists in determining the TSD of menstrual bloodstains. This study demonstrates how Raman spectroscopy effectively analyzes biological samples like menstrual blood, showing similar aging patterns to those of peripheral blood and provides proof-of-concept models for determining the TSD of menstrual blood. While this work shows promising results for creating a universal model for bloodstain age determination, further testing with more donors needs to be conducted before the implementation of this method into forensic practice.

Evaluating the effectiveness of a 5-day training on science-based methods of interrogation with U.S. federal, state, and local law enforcement investigators.

Evaluating the effectiveness of a 5-day training on science-based methods of interrogation with U.S. federal, state, and local law enforcement investigators.

Recommendations for Improving the Use of Direct-To-Consumer Genetic Testing Databases in Law Enforcement Investigations

Prisoners are some of the most vulnerable populations in our society today, often relinquishing to the state everything from medical autonomy to family support. In a system where wrongful convictions are not unheard of, it is critical that we preserve the civil rights of investigative subjects wherever possible. Law enforcement agencies in the United States have increasingly begun using direct-to-consumer recreational genetic databases as a tool to enable forensic investigations. These commercial genetic testing companies analyze polymorphisms in DNA to isolate genealogical information, medical data, and other traits. Traditionally, law enforcement has been restricted to the use of matching repeating sequences in non-coding sections of DNA. However, through services like GEDMatch, law enforcement has gained access to single nucleotide polymorphism (SNP) markers from upwards of 25 million consumers throughout the world. This rapidly developing technology must be regulated to ensure that consumers, as well as blood relatives of consumers, are not unfairly targeted by investigations. With studies indicating that DNA is typically reported as the single most important piece of evidence to jurors, it is in the best interests of policymakers to ensure that the DNA data is both accurate and used fairly. First, we will provide a background of the technology and regulation of direct-to-consumer (DTC) genetic testing databases in law enforcement. Second, we propose a mechanism by which states might legislate the appropriate use of these databases by law enforcement by limiting access and enforcing a double-blind system. This paper lays out the background and policy proposal for a requirement of direct-to-consumer genetic testing companies to communicate the possibility and type of information shared with law enforcement, and a framework by which policymakers can ensure unbiased and minimally intrusive use by law enforcement.

Peculiarities of certain investigative actions and procedural guidance of the prosecutor during martial law

On 24 February 2022, a full-scale war broke out and martial law was introduced throughout Ukraine by Presidential Decree No. 64/2022 in connection with the military aggression of the Russian Federation. The efficiency and effectiveness of criminal proceedings during the martial law regime depends on the quality of criminal procedural rules.
 The armed conflict initiated and supported by the Russian Federation on the territory of Ukraine since 2014 has created new challenges for the system of both international and national justice. The article draws attention to the fact that with the introduction of martial law in Ukraine on 24 February 2022 in connection with the military aggression of the Russian Federation, a number of significant changes were made to both the «military» section IX-1 and other sections of the Criminal Procedure Code of Ukraine. The nature of violations of these provisions requires a different approach not only at the level of legal qualification, but also in the process of organisation and procedural guidance of the pre-trial investigation by the prosecutor.
 The author emphasizes that the testimony obtained during the interrogation of a suspect, including simultaneous interrogation of two or more already interrogated persons, in criminal proceedings conducted under martial law may be used as evidence in court only if a defence counsel participated in such interrogation and the course and results of the interrogation were recorded using available video recording equipment.
 The author draws attention to the fact that prosecutors who provide procedural guidance in criminal proceedings concerning crimes committed in the context of armed conflict should record the testimony of victims and key witnesses, in particular, on issues relating to the role of the Russian Federation and its subordinate formations in the context of armed conflict on the territory of Ukraine, including the temporarily occupied territories.
 Pre-trial investigations of criminal offences committed in the context of armed conflict can take a long time, and it is therefore important for law enforcement investigators and prosecutors to take measures to preserve information, primarily the testimony of victims and witnesses.
 When organising procedural guidance, prosecutors should take into account the peculiarities of conducting and recording the course and results of investigative (detective) actions under martial law.

Building Rapport in Interviews with Adolescent Trafficking Victims

AbstractThough much is known about children's sexual abuse disclosure, less attention has been directed towards disclosure in other types of youthful victims, especially those who may be reluctant to tell due to either normative development or victims' specific experiences. Trafficked youth, particularly those who are adolescents, represent one such group. Understanding how suspected youth trafficking victims are questioned by authorities, especially with respect to establishing rapport and trust, is important for informing professionals how to effectively question this unique population of victims to overcome their reluctance. We examined transcripts of interviews conducted by federal interviewers (n = 12,653 question‐answer turns across 33 interviews) and police (n = 4,972 question‐answer turns across 14 interviews) with trafficked youth between the ages of 12 and 18. Interviews were reliably coded for the length of pre‐substantive questioning, provision of instructions and ground rules, and use of rapport building and supportive strategies. Federal interviewers used pre‐substantive instructions and built rapport with potential victims more often than police did. Also, and although infrequently used overall, supportive interviewing strategies were evident more often by federal interviewers than police. Results provide much‐needed knowledge about how law enforcement investigators interview and elicit disclosures from vulnerable populations of adolescent victims.

Person reference in police interviews: A case study of domestic violence in Indonesia

Person reference plays a critical role in judicial discourse, influencing perceptions of impartiality and respect. Person reference can express partiality or respect, either through solidarity with, or the humanization of, witnesses, victims, suspects, or defendants in law enforcement settings. Furthermore, it is important to acknowledge that verbal violence or dehumanization can sometimes be perceived as a manifestation of impartiality, when individuals employ words that inflict harm upon others. This study employs a qualitative approach to examine the utilization of person reference by two police investigators during their interview of a suspect involved in a domestic violence incident. The data consisted of transcripts from two experimental setup interviews conducted by two police investigators with one adult individual assuming the role of a suspect. The research revealed that law enforcement investigators employed formal nomination categories during interviews in order to establish a significant level of separation between the investigating officers and the individual under investigation. The present study revealed that two police investigators made efforts to humanize the suspect. Nevertheless, the transition from using the honorifics "Bapak/Pak (Mr/Sir)" as a sign of reverence for older males, to employing the term "Saudara (metaphorical brother/sister)" in a legal setting, indicating a lack of familiarity in the connection, results in an escalation of social distance. This realization advances our knowledge of the subtle ways in which linguistic decisions can affect law enforcement interactions, offering valuable implications for improving the fairness and effectiveness of judicial discourse.

The next phase of identifying illicit activity in Bitcoin

AbstractIdentifying illicit behavior in the Bitcoin network is a well‐explored topic. The methods proposed over time have generated great insights into the deanonymization of the Bitcoin user base through the clustering of inputs and outputs. With advanced techniques being deployed by Bitcoin users, these heuristics are now being challenged in their ability to aid in the detection of illicit activity. In this paper, we provide a comprehensive list of methods deployed by malicious actors on the network and illicit transaction mining methods. We detail the evolution of the heuristics that are used to deanonymize Bitcoin transactions. We highlight the issues associated with conducting law enforcement investigations and propose recommendations for the research community to address these issues. Our recommendations include the release of public data by exchanges to allow researchers and law enforcement to further protect the network from malicious users. We recommend the enhancement of current heuristics through machine learning methods and discuss how researchers can take the fight head‐on against expert cybercriminals.

Investigative fatigue: how sleep-circadian factors shape criminal investigations.

Investigating criminal complaints and identifying culprits to be prosecuted in the court of law is an essential process for law-enforcement and public safety. However, law-enforcement investigators operate under very challenging conditions due to stressful environments, understaffing, and public scrutiny, which factors into investigative errors (e.g. uncleared cases). This paper argues that one contributing factor to investigative failures involves sleep and circadian disruption of investigators themselves, known to be prevalent among law-enforcement. By focusing on investigative interviewing, this analysis illustrates how sleep and circadian disruption could impact investigations by considering three broad phases of (1) preparation, (2) information elicitation, and (3) assessment and corroboration. These phases are organized in a framework that outlines theory-informed pathways in need of empirical attention, with special focus on effort and decision-making processes critical to investigations. While existing evidence is limited, preliminary findings support some elements of investigative fatigue. The paper concludes by placing investigative fatigue in a broader context of investigative work while providing recommendations for future research throughout. This paper is part of the Sleep and Circadian Health in the Justice System Collection.

The Paradox of Child's Diversion Policy in Conflict with the Law in the Indonesian Child Criminal Justice System

This research aims to examine the paradox of implementing the diversion policy for children in conflict with the law in student brawl cases in DKI Jakarta. The research uses a qualitative approach with a case study method. Case analysis uses forecasting analysis framework by William Dunn (2003) and Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis by Chermack and Kasshanna (2007). There are three conclusions from this research. First, the problems of the diversion policy for children in conflict with the law are generally not caused by primordial factors but are caused by law enforcement investigators who often do not follow the mandate of the Law on The Child Criminal Justice System to determine child diversion. This is because the police apply criminal offenses based on the perpetrator's actions and can consider the recommendations of the Community Counselor of the Correctional Center. Second, there is a paradox in the implementation of the diversion policy for children in conflict with the law, starting from the high use of the Emergency Law in the Indonesian Legal System, the low competence of law enforcement officers in implementing the diversion policy for children in conflict with the law, terminating investigations without involving Community Counselor of the Correctional Center, to carrying out detention in correctional centers that are not child-friendly. Third, based on forecasting and SWOT analysis, it is necessary to transform juvenile justice legal policies in the future, especially increasing competency of the law enforcement officers, ensuring the availability of child-friendly infrastructure, supporting the child in conflict with the law advocacy and extensifying community-based policing.

Is combatting money laundering an integrity issue? Insights from Nigeria

PurposeThis study aims to determine how integrity influences money laundering combatting.Design/methodology/approachA qualitative approach using methodological triangulation was used to answer the question to describe and understand the phenomena from the participants’ perspective. Data was gathered with a semi-structured questionnaire, observation and field notes.FindingsAnalysis revealed that 93% of law enforcement investigators believe integrity is required to combat money laundering. They also observed that integrity is needed for the political environment, institutions and their personnel or officers.Practical implicationsThere is a need for integrity in the economy’s public and private sectors to combat money laundering effectively. Integrity must be present in the political environment, institutions and personnel. Hence, a recommendation is to appoint chief integrity officers in all stakeholder organisations.Originality/valueThis study is among the few research that covers the area of integrity and its influence on combatting money laundering from law enforcement investigators’ perspective.

The Evolution of Forensic Genomics: Regulating Massively Parallel Sequencing.

Forensic genomics now enables law enforcement agencies to undertake rapid and detailed analysis of suspect samples using a technique known as massively parallel sequencing (MPS), including information such as physical traits, biological ancestry, and medical conditions. This article discusses the implications of MPS and provides ethical analysis, drawing on the concept of joint rights applicable to genomic data, and the concept of collective moral responsibility (understood as joint moral responsibility) that are applicable to law enforcement investigations that utilize genomic data. The widespread and unconstrained use of this technology without appropriate legal protections of individual moral rights and associated accountability mechanisms, could potentially not only involve violations of individual moral rights but also lead to an unacceptable shift in the balance of power between governments and the citizenry. We argue that in light of the rights of victims and the security benefits for society, there is a collective moral responsibility for individuals to submit their DNA to law enforcement and for MPS to be used where other, less invasive techniques are not effective. However, this application should be limited by legislation, including that any data obtained should be directly relevant to the investigation and should be destroyed at the conclusion of the investigation.

Estimation of bloodstain deposition time within a 24-h day-night cycle with rhythmic mRNA based on a machine learning algorithm

Estimating the time that bloodstains are left at a crime scene can provide invaluable evidence for law enforcement investigations, including determining the time of the crime, linking the perpetrator to the crime scene, narrowing the pool of possible suspects, and verifying witness statements. There have been some attempts to estimate the time since deposition of bloodstains, i.e., how much time has passed since the bloodstain was left at a crime scene. However, most studies focus on the time interval of days. As far as we know, previous study have been conducted to estimate the deposition time of blood within a 24-h day-night cycle. To date, there is a lack of studies on whether rhythmic mRNA of blood is suitable for bloodstain samples. In this study, we estimated the bloodstain deposition time within a 24-h day-night cycle based on the expression of messenger RNAs (mRNAs) by real-time quantitative polymerase chain reaction. Bloodstain samples were prepared from eight individuals at eight time points under real and uncontrolled conditions. Four mRNAs expressed rhythmically and were used to construct a regression model using the k-nearest neighbor (KNN) algorithm, resulting in a mean absolute error of 3.92 h. Overall, using the rhythmic mRNAs, a machine learning model was developed which has allowed us to predict the deposition time of bloodstains within the 24-h day-night cycle in East Asian populations. This study demonstrates that mRNA biomarkers can be used to estimate the bloodstain deposition time within a 24-h period. Furthermore, rhythmic mRNA biomarkers provide a potential method and perspective for estimating the deposition time of forensic traces in forensic investigation. Case samples in forensic analysis are usually limited or degraded, so the stability and sensitivity of rhythmic biomarkers need to be further investigated.

Inductive and transductive link prediction for criminal network analysis

The identification of potential offenders, who are more likely to form a new group and co-offend in a crime, plays an essential role in narrowing down law enforcement investigations and improving predictive policing. Once a crime is committed, focusing on linking it to previously reported crimes and reducing the inspections based on shreds of evidence and the behavior of offenders can also greatly help law enforcement agencies. However, classical investigative techniques are generally case-specific and rely mainly on police officers manually combining information from different sources. Therefore, automatic methods designed to support co-offender research and crime linkage would be beneficial. This paper proposes two graph-based machine learning frameworks to address these issues based on a burglary use case, the first being transductive link prediction, which seeks to predict emergent links between existing graph nodes (which represent offenders or criminal cases), and the other being inductive link prediction, where connections are found between a new case and existing nodes. Our experimental results show a prediction accuracy of 68.5% in co-offender prediction, a 75.83% predictive accuracy for transductive crime linkage, and up to 74.8% accuracy in inductive crime linkage.