Forensic Evidence Research Articles

Comparative Analysis of Forensic Digital Evidence on Android Smartphone based Instant Messaging Using NIST Framework

Smartphones are currently experiencing rapid development along with technological developments. The rapid development of smartphones is also followed by the increasing use of social media and instant messaging. One of the well-known instant messaging applications, namely Whatsapp, issues a notification that its user content, whether uploading, storing, receiving or sending anything on WhatsApp, the company can use, reproduce, and display or distribute it. With this notification, WhatsApp users switch to more private instant messaging, namely Telegram and Signal Messenger. This study uses the National Institute of Standards and Technology (NIST) method, namely collection, examination, analysis,presentation. This study uses two smartphones with root and non-root conditions that have installed the whatsapp, telegram, and signal messenger applications. The case used in this study is a narcotics sale and purchase transaction. Digital evidence was obtained using four forensic tools, namely MOBILedit Forensic Express,Oxygen forensics, Belkasoft Evidence, and Magnet Axiom. This study produces digital evidence in the form of chat files, images, videos, perpetrator accounts,contacts, locations and conversations that have been deleted from smartphone devices. The calculation of the index result from the percentage of evidenceobtained by the WhatsApp application on a smartphone with root conditions usingthe forensic tool Oxygen forensic got the result, namely 50%. Telegram gets 50%results using Oxygen forensic with root conditions. While the signal gets the result,which is 30% using MOBILedit with root conditions.

Ethanolysis of nitrogen mustards: A novel strategy for nitrogen mustard identification in environmental matrices by liquid chromatography-electrospray ionization-tandem mass spectrometry.

Nitrogen mustards (NMs) are blistering chemical warfare agents. The ability to detect NMs in environmental samples is very important for obtaining forensic evidence. The most common analytical techniques for NM detection are gas chromatography-mass spectrometry, which detects NMs in their intact form but is disadvantaged by high limits of detection (LODs), and liquid chromatography-electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS) of their hydrolysis products, which do not provide robust evidence to support NM use. We developed a novel approach to detect and identify NMs using LC/ESI-MS/MS after chemical derivatization. The method is based on ethoxide-promoted ethanolysis prior to analysis. The effects of reaction time, temperature, ethoxide concentration and chromatography behavior were studied and optimized. In the developed procedure, 0.1% (v/v) sodium ethoxide solution is added to the NMs in ethanol and agitated for 2h at 50°C, followed by LC/ESI-MS/MS, without any other pretreatment. The ethanolysis reaction efficiencies were evaluated in ethanolic extracts from soil, asphalt, and ethanol contaminated with 0.5% (v/v) diesel fortified with NMs at a five-point calibration curve. The calibration curves showed good linearity in the range of 0.05-1ng/mL, with an R2 value of 0.99, and were similar to those of LC/MS-grade ethanol, with almost no observable matrix effects. The derivatization products were stable at room temperature, with LODs of 10pg/mL, in all investigated extracts. Through this newly developed strategy, the derivatization of active NMs by ethanolysis was achieved for the first time, and these derivatization products can serve as specific indicators for the use and presence of NMs. The methodology can also verify trace levels of NM chemical warfare agents collected in war or terror scenarios in forensic investigations.

Do Concerns About Police Reporting Vary by Assault Characteristics? Understanding the Nonreporting Decisions of Sexual Assault Victims Who Utilize Alternative Reporting Options.

Forensic nurses routinely provide services to sexual assault victims who are uncertain about reporting their assault to police. The purpose of this study was to determine whether assault characteristics are related to the concerns about police reporting expressed by sexual assault victims who have forensic evidence collected but do not report their assault to police at that time. We analyzed medical records of patients who received services at a hospital-based forensic nursing program between 2010 and 2021. Records were included if a sexual assault evidence kit was collected, the patient declined to report the assault to police, and the patient completed a nonreport sexual assault evidence kit supplement form that included a question asking why they chose not to report the assault ( N = 296). We qualitatively analyzed patients' reasons for not reporting the assault and then used two-variable case-ordered matrices and chi-square analyses to explore relationships between reasons for not reporting and assault characteristics. Identified reasons for not reporting included lacking information about the assault, fear of harm/retaliation, and self-blame/minimization. Physical force, drug/alcohol consumption, and victim-offender relationship were related to patients referencing lacking information and fearing harm/retaliation as reasons for not reporting, but not related to the frequency of patients referencing self-blame/minimization. Results indicate that assault characteristics are related to reasons for not reporting at the time of the medical forensic examination. Being aware of these relationships may help forensic nurses provide patient-centered services and anticipatory guidance.

Misuse of statistical method results in highly biased interpretation of forensic evidence in

Misuse of statistical method results in highly biased interpretation of forensic evidence in

Advancing automobile identification and brand discrimination from tyre rubber through Machine learning algorithms for forensic investigations

Criminal instances involving collision accidents, hit-and-run incidents, abduction, hostage-taking, and the unauthorised transit of forbidden items generally include evidence involving rubber traces from automobile tyres. These traces can be located on the road surface, in clothing, on the victim(s) themselves, or on items as skid marks following sudden stopping and spinning around. These traces serve as crucial evidence by reducing the range of suspects by revealing linkages between the getaway vehicle, the site of the crime, and the perpetrator through the tyre's brand, producer, or origin. This study offered a way for classifying 220 tyre rubber samples from different brands using various machine learning algorithms in PyCaret in conjunction with rapid and non-destructive ATR-FTIR spectroscopy equipped with diamond crystal. On spectral information from ATR-FTIR, pre-processing tools such as baseline correction, smoothing, derivatization, and normalisation were also implemented prior to machine learning. This approach has the potential to be advantageous for efficiently and non-destructively identifying rubber traces as forensic evidence and for facilitating brand recognition of automobile tyres.

A template Bayesian network for combining forensic evidence on an item with an uncertain relation to the disputed activities

Most of the forensic evidence evaluations given activity level propositions are centered around an item which is assumed to be linked to an alleged activity. However, the relation between an item of interest and an activity may be contested. This study presents a template Bayesian network (BN) for the evaluation of transfer evidence given activity level propositions considering a dispute about the relation of an item to one or more activities. The template BN includes a set of association propositions that enables the combined evaluation of evidence concerning alleged activities of the suspect and evidence concerning the use of an alleged item in those activities. Since the two types of evidence are often from different forensic disciplines, the BN is especially useful in interdisciplinary casework. Throughout the paper, we use a fictive case example that captures the essence of cases for which the template model can be used. The template BN provides a flexible starting point that can be adapted to specific case situations and supports structured probabilistic reasoning by a forensic scientist.

The Preparation of Tape Lift Samples for the Study of Subvisible and Nanoparticles

Tape lifts are commonly used as a substrate for the collection of microscopic trace evidence. While traces such as fibers, glass, and paint can generally be readily recognized by stereomicroscopy, these larger particles often represent a minor, to trace fraction of the total particulate load on a given lift. In contrast, smaller particles (broadly categorized as dust), which are frequently the dominant component on the tape, are less commonly exploited as forensic evidence. These particles, which for the purposes of this article, may range in size from hundreds of micrometers down to nanometers (i.e., subvisible) are difficult, or sometimes impossible to see, much less characterize, by stereomicroscopy. Such particles also present challenges to isolate, manipulate, and analyze. In addition, when collected on tape lifts, as is the case in many forensic examinations, such particles become trapped in an adhesive matrix, further complicating attempts to isolate all but the largest particles for subsequent analyses.

Case study: using forensic data analysis to link crime scenes

Burglary crimes inflict a significant toll on society, both financially and psychologically. Most of these cases are never solved, many times because no visible signs of entry or forensic evidence are found at the scene. In this report, we detail a police case involving a series of burglaries in Israel, all of which lacked any visible signs of forced entry. Thirteen burglaries were initially linked by the so-called forensic intelligence method and the analysis of additional forensic data obtained during the inspection of the scene and in the forensic laboratory. Linking seemingly unrelated crime scenes through forensic data analysis can increase the effectiveness of case investigations.

The Use of Forensic Evidences in Investigations and Prosecution in International Criminal Proceedings. Case Study of International Criminal Court (ICC)

From 1990s, a rising number of international and hybrid criminal tribunals and since 2002, the International Criminal Court have conducted various investigations on international crimes including crime against humanity, genocide and war crimes in various countries worldwide. These judicial organs have repeatedly relied upon witness’s testimonies, information and assistance from a wide variety of sources including governments, journalists, peacekeepers, human rights researchers and intelligence specialists and few forensic scientists, wherein some of these information and reports were driven by politics. Even though such information were very benefitting “there have also been many mishaps, misunderstandings in terms of differentiating information and evidence and missed opportunities in view of finding out the truth in way that information that could potentially have been of great use to criminal cases was lost or was collected or preserved in a manner that made it unusable at trial.” In today’s era, where there is a remarkable technological development in forensic science, it is time to use forensic methods in investigation of international crimes since a number of scientific and technological advances have improved the ability to document large-scale crimes with efficiency and precision. Yet, only in recent years have international criminal courts and other fact-finding institutions begun to embrace these innovations. There is a need of forensic science in investigating and prosecuting offenders of atrocities than traditional use of testimonies which are not easy to be relied on but still some legal and administrative issues still hinder the successful use of forensic evidences in investigating and prosecuting in international criminal proceedings. The present research focused on the practical use of forensic evidences like; pathology and DNA in exhumation of mass grave for determination of cause, manner and mechanism of death but to locate, excavate and exhume mass graves to produce forensic evidences of atrocities and to returning victims to loved ones and also discussed as tools for justice, humanitarian and documentation.The research also revealed the problems which are not only limited to the legal challenges of insufficiency of forensic evidence admissibility regulations and their maintenance of chain of custody, but also there are administrative issues like, lack of fund to be used during forensic investigation activities including, crime scene examination, collection of evidence and laboratory International Journal of Forensic Sciences 2 Thierry MB and Fred K. The Use of Forensic Evidences in Investigations and Prosecution in International Criminal Proceedings. Case Study of International Criminal Court (ICC). Int J Forens Sci 2024, 9(2): 000380. Copyright© Thierry MB and Fred K. examination of forensic evidence and all these can lead to unnecessary complications and prolongation criminal proceedings in international criminal court hence breach of fair trial principle. Finally, the research proposed reforms by establishing specific regulations related to the admissibility of forensic evidences in international criminal proceedings and chain of custody of forensic evidences as well as harmonizing the standard operating procedure of forensic investigation to regulate scientific investigation activities including, Crime Scene Management, Evidence Collection, Examination of forensic evidences and forensic expert report writing in investigation and prosecution of international criminal proceeding and also detailed mandate to solve administrative issues.

Challenges in Modeling, Interpreting, and Drawing Conclusions from Images as Forensic Evidence

Challenges in Modeling, Interpreting, and Drawing Conclusions from Images as Forensic Evidence

To Study the Unique Characteristics of Cut Mark on Clothes with a Suspected Knife on the Basis of Microscopic Examination (Optical Comparator): A Case Report

Forensic physics plays a crucial role in cut mark examination, particularly in the analysis of tool marks, including those created by sharp objects like knives or other cutting instruments. The examination of cut marks involves the application of various principles and techniques from physics to understand the nature, characteristics, and potential source of the marks. In the State of Meghalaya, a numbers of cases are received to determine whether the cut marks on clothes are caused or cut by the suspected sharp object. This is predominantly occurring due to conflicts among individuals or groups often involving the use of hard objects or sharp weapons. The prevalence of such cases necessitates a closer examination of cut marks on clothing items as crucial forensic evidence. However, due to improper collection, preservation and packaging of exhibits has cause a potential hinder for the Forensic Expert's ability to provide a conclusive opinion. This study sheds light on the frequent occurrence of cases wherein cut marks on clothing serve as pivotal forensic evidence. Through a systematic scientific approach, this paper elucidates the significance of identifying and interpreting such distinctive features in forensic investigation. This study endeavours to empower forensic experts, enabling them to provide more reliable and insightful conclusions in cases involving cut mark examinations. The proposed improvements not only strengthen the forensic framework but also contribute to the effective resolution of cases involving attempted harm in this region.

Demonstrative Evidence and the Use of Algorithms in Jury Trials

We investigate how the use of bullet comparison algorithms and demonstrative evidence may affect juror perceptions of reliability, credibility, and understanding of expert witnesses and presented evidence. The use of statistical methods in forensic science is motivated by a lack of scientific validity and error rate issues present in many forensic analysis methods. We explore what our study says about how this type of forensic evidence is perceived in the courtroom – where individuals unfamiliar with advanced statistical methods are asked to evaluate results in order to assess guilt. In the course of our initial study, we found that individuals overwhelmingly provided high Likert scale ratings in reliability, credibility, and scientificity regardless of experimental condition. This discovery of scale compression - where responses are limited to a few values on a larger scale, despite experimental manipulations - limits statistical modeling but provides opportunities for new experimental manipulations which may improve future studies in this area.

From understanding to justifying: Computational reliabilism for AI-based forensic evidence evaluation

Techniques from artificial intelligence (AI) can be used in forensic evidence evaluation and are currently applied in biometric fields. However, it is generally not possible to fully understand how and why these algorithms reach their conclusions. Whether and how we should include such ‘black box’ algorithms in this crucial part of the criminal law system is an open question that has not only scientific but also ethical, legal, and philosophical angles. Ideally, the question should be debated by people with diverse backgrounds.Here, we present a view on the question from the philosophy of science angle: computational reliabilism (CR). CR posits that we are justified in believing the output of an AI system, if we have grounds for believing its reliability. Under CR, these grounds are classified into ‘reliability indicators’ of three types: technical, scientific, and societal. This framework enables debates on the suitability of AI methods for forensic evidence evaluation that take a wider view than explainability and validation.We argue that we are justified in believing the AI's output for forensic comparison of voices and forensic comparison of faces. Technical indicators include the validation of the AI algorithm in itself, validation of its application in the forensic setting, and case-based validation. Scientific indicators include the simple notion that we know faces and voices contain identifying information along with operationalizing well-established metrics and forensic practices. Societal indicators are the emerging scientific consensus on the use of these methods, as well as their application and interpretation by well-educated and certified practitioners. We expect expert witnesses to rely more on technical indicators to be justified in believing AIsystems, and triers-of-fact to rely more on societal indicators to believe the expert witness supported by the AIsystem.

The Critical Importance of Impartiality in examining forensic evidence and reporting forensic findings to the Judiciary in South Africa

The Critical Importance of Impartiality in examining forensic evidence and reporting forensic findings to the Judiciary in South Africa

Development of Latent Fingerprints on Different Types of Gloves by Using Physical and Chemical Methods

Fingerprints are a foundation of forensic evidence collected at crime scenes. But what if the perpetrator tries to be clever and wear gloves? Does this automatically mean no fingerprints will be found? Not quite. Latex gloves abandoned at crime scenes can be potential evidence that leaves the perpetrator's hidden fingerprints behind. However, despite their potential, gloves have proven to be a tricky surface for fingerprint development. This study explores the possibility of extracting fingerprints from gloves left behind by criminals. Sweat residues, dirt, and tiny particles trapped on the glove's inner surface can transfer a latent fingerprint, even if it's smudged. This smudged print can still hold valuable clues about the perpetrator. The study aims to observe the effectiveness of fingerprint development on various glove materials: latex, nitrile, cotton, plastic, and silicone. For this, a range of physical and chemical techniques were employed to reveal these hidden prints. Specialized chemicals like ninhydrin, iodine fuming, silver nitrate, Sudan black, and gentian violet were used to make the latent prints visible. Noninvasive approaches like fingerprint powders were also used to develop latent prints on the surface of gloves. This research highlights the ingenuity of forensic science in uncovering evidence even when criminals attempt to mask their identities.

SHARD-FEMF: Adaptive Forensic Evidence Management Framework using Blockchain Sharding and IPFS

Blockchain technology is a groundbreaking and highly secure decentralized digital ledger used to record and store transactions across a network of computers. Its primary purpose is to safeguard, monitor, and oversee digital assets, providing robust protection against unauthorized tampering, revisions, or deletions. It serves as an immutable and tamper-resistant ledger ideal for storing digital evidence, enabling the tracking of evidence’s origins while strictly controlling access to authorized individuals. Current evidence management systems lack essential functionalities, such as authenticating intermediate user access and efficiently transferring evidence access between users. These systems also rely on the Base64 algorithm, which presents challenges related to storage capacity, time delays, scalability, and transaction throughput. To address these limitations, this research introduces an innovative solution: The integration of the Base64 scheme with sharding and the Interplanetary File System (IPFS). This integration is designed to bolster transaction performance, scalability, and throughput. The Base64 scheme plays a pivotal role by encrypting image evidence, securely housing it within the blockchain network. Concurrently, IPFS decentralizes the storage of these images, thereby optimizing memory usage and enhancing transaction throughput within the blockchain environment. Experimental results showcase the efficacy of the proposed SHARD-FEMF, demonstrating a 25% improvement in memory utilization, a 21.5% reduction in gas utilization, and a 23% enhancement in transaction scalability compared to the existing Base64 scheme. Through the combined utilization of sharding and IPFS, the SHARD-FEMF framework represents a significant advancement in efficient forensic evidence management leveraging blockchain technology

The state of scientific research on the concept of forensic evidence

The state of scientific research on the concept of forensic evidence

Microwave-assisted extraction, separation, and chromogenic detection of laced marijuana for presumptive point-of-interdiction testing.

Presumptive drug screening enables timely procurement of search and arrest warrants and represents a crucial first step in crime scene analysis. Screening also reduces the burden on forensic laboratories which often face insurmountable backlogs. In most scenarios, on-site presumptive drug screening relies on chemical field tests for initial identification. However, even when used appropriately, these test kits remain limited to subjective colorimetric analysis, produce false positive or negative results with excessive sample quantities, and are known to cross-react with numerous innocuous substances. Previous efforts to develop microfluidic devices that incorporate these chromogenic indicator reagents address only a few of the many challenges associated with these kits. This is especially true for samples where the drug of interest is present as a lacing agent. This work describes the development of a centrifugal microfluidic device capable of integrating facile sample preparation, by way of a 3D printed snap-on cartridge amenable to microwave assisted extraction, followed by chromatographic separation and chromogenic detection on-disc. As cannabis is among the most widely used controlled substance worldwide, and displays strong interference with these indicator reagents, mock samples of laced marijuana are used for a proof-of-concept demonstration. Post extraction, the microdevice completes high throughput metering just prior to simultaneous reaction with four of the most commonly employed microchemical tests, followed by objective image analysis in CIELAB (a device-independent color model). Separation and recovery of a representative controlled substance with 93% efficiency is achieved. Correct identification, according to hierarchical cluster analysis, of three illicit drugs (e.g., heroin, phencyclidine, and cocaine) in artificially laced samples is also demonstrated on-disc. The cost effective microdevice is capable of complete automation post-extraction, with a total analysis time (including extraction) of <8 min. Finally, sample consumption is minimized, thereby preventing the complete destruction of forensic evidence.

Prior Art: Forensic Evidence of Musical Originality in Copyright Litigation

Prior Art: Forensic Evidence of Musical Originality in Copyright Litigation

INFRARED THERMOGRAPHY IMAGE BASED CLASSIFICATION OF SOIL DIRT AND FABRIC

Soil is the substance most likely to meet nature and dirt people, vehicles, and clothing, especially in outdoor. Both source material and soil samples can be damaged during industrial and criminal investigations. Therefore, there is a need for detection, examination, and identification systems that can minimize contact with forensic evidence and provide accurate results with fewer samples. The study aims to determine the type of soil using a low-cost, easily accessible, and highly sensitive system that can be used easily without interference from the surface properties of the textile or destruction of the structure of the dirt. The working sites and areas of samples to be collected were determined according to the purpose of the study. In this context, samples of the most common soil types were taken from the lands in the Aegean Region of Turkey. Different types of substances were applied and dirtying on the collected samples. The newly formed samples were heated with a heating surface and allowed to cool. During this process, a thermal video was recorded, and feature extraction was performed. 165 samples were obtained from 55 tests. As a result, it is seen that the proposed method can detect samples with 97% accuracy.