Forensic Sci., Volume 4, Issue 1 (March 2024) – 11 articles

Recent research has seen a rapid expansion in the reference to front-end forensics as an indication of the untapped value of forensic science. While some of these contributions have centered on development of forensic intelligence from a single area of investigation, others call for a more fundamental change in the relationship between crime laboratories and policing, particularly relating early laboratory analysis with big datasets to provide leads to investigators. We highlight several recently implemented tactical strategies of crime laboratories that contribute to the body of forensic intelligence. Beyond the scientific gains from these tactical applications, the corresponding details on associated efficiencies, costs, time savings, and quality improvements offer insights towards patterns of success for the community of crime laboratories. Further details expand an interpretation of what constitutes success with an eye on the contributions of the crime laboratory towards public health, safety, and protection of the innocent in addition to societal gains from conviction of the guilty. The economic interpretation of the value provided by the forensic laboratory assists in the cost–benefit review of strategic and tactical decisions and supports the justification for laboratory public funding with measures of the return on investment from public support of the forensic laboratory. Examples of the cost savings from crimes avoided include the returns from testing the backlog of unsubmitted sexual assault kits with USD 81 of costs avoided for each USD 1 spent to high-efficiency laboratories achieving gains of USD 646 for each UD 1 spent on de novo case submissions. Full article

From the information forensics point of view, it is important to correctly classify between natural images (outputs of digital cameras) and computer-graphics images (outputs of advanced graphics rendering engines), so as to know the source of the images and the authenticity of the scenes described in the images. It is challenging to achieve good classification performance when the forensic classifier is tested on computer-graphics images generated by unknown rendering engines and when we have a limited number of training samples. In this paper, we propose two simple yet effective methods to improve the classification performance under such challenging situations, respectively based on data augmentation and the combination of local and global prediction results. Compared with existing methods, our methods are conceptually simple and computationally efficient, while achieving satisfying classification accuracy. Experimental results on datasets comprising computer-graphics images generated by four popular and advanced graphics rendering engines demonstrate the effectiveness of the proposed methods. Full article

The Investigator ESSplex SE QS Kit (Qiagen) is a next-generation polymerase chain reaction (PCR) kit that, in 60 min, amplifies 17 Short Tandem Repeat (STR) markers, including the five European Standard Set (ESS) loci (D10S1248, D12S391, D1S1656, D22S1045, D2S441), the SE33 marker, and the locus Amelogenin for sex determination. Two quality sensors (QS1 and QS2) are also co-amplified to check PCR performance. Since forensic laboratories carry out hundreds of DNA typings annually, we verified the kit’s performance using half reaction volumes with the aim of improving the number of samples that may be amplified with a single kit and consequently reducing laboratory costs. In the present study, intended as a technical note rather than internal validation, some control samples (oral swabs) with known DNA profiles and 40 real casework samples were analyzed. We observed that reducing the total reaction volume, while keeping all component ratios unaltered, yields DNA profiles comparable to those obtained using standard reaction volumes and with allele peaks higher than those with regular volumes. Using half volumes for PCR amplification enables the analysis of a larger number of samples compared to the standard protocol, thereby reducing laboratory costs without compromising the quality of the analysis. Full article

The Cyber Forensics Behavioral Analysis (CFBA) model merges Cyber Behavioral Sciences and Digital Forensics to improve the prediction and effectiveness of cyber threats from Autonomous System Numbers (ASNs). Traditional cybersecurity strategies, focused mainly on technical aspects, must be revised for the complex cyber threat landscape. This research proposes an approach combining technical expertise with cybercriminal behavior insights. The study utilizes a mixed-methods approach and integrates various disciplines, including digital forensics, cybersecurity, computer science, and forensic psychology. Central to the model are four key concepts: forensic cyberpsychology, digital forensics, predictive modeling, and the Cyber Behavioral Analysis Metric (CBAM) and Score (CBS) for evaluating ASNs. The CFBA model addresses initial challenges in traditional cyber defense methods and emphasizes the need for an interdisciplinary, comprehensive approach. This research offers practical tools and frameworks for accurately predicting cyber threats, advocating for ongoing collaboration in the ever-evolving field of cybersecurity. Full article

Forensic soil analysis is crucial in criminal investigations, necessitating robust analytical methodologies for an accurate discrimination of soil types and origins. This study explored the discrimination efficiency of thermogravimetric and differential scanning calorimetric analyses of Inceptisol, reddish Oxisol, and yellowish Oxisol soils from Brazil’s Cerrado region. Ninety air-dried soil samples collected at various locations underwent thermal analysis, focusing on mass loss of gibbsite, goethite, and kaolinite at specific temperatures. The log-transformed data were submitted to principal component analysis, nonmetric multidimensional scaling, and cluster analysis. The thermogravimetry emerged as a highly discriminatory tool, effectively delineating between soil types, and even detecting spatial variations. In contrast, the differential scanning calorimetry exhibited limited discriminatory power. The findings underscore the thermogravimetric potential as a valuable technique in soil forensics, providing critical insights into composition and spatial variations essential for criminal investigations. This study highlights the need for further research to explore synergies with complementary techniques, aiming to enhance forensic discrimination across diverse soil types and geographic contexts. The objective representation of results in this abstract emphasizes the significance of thermogravimetry in advancing forensic analysis of soil vestiges. Full article

Selecting the optimal sampling method is an essential component of the DNA analysis process. Errors or omissions in targeting and gathering relevant samples can significantly reduce the likelihood of obtaining a valuable DNA profile, affecting the profile’s quality and evidential value and ultimately hindering its ability to support the justice system. While DNA typing techniques have become significantly more sensitive in recent years, there is an ongoing need for further advancements in the recovery of DNA from crime scenes. It is essential to improve the accuracy and reliability of forensic investigations, particularly in cases where only tiny amounts of DNA are present, such as touch DNA samples or degraded forensic evidence. Parameters, including swab material, type of substrate, and swabbing protocol, that influence the efficiency of a swab are discussed in this review. This is followed by a literature review of studies that have compared swab types and/or other sampling conditions. While swabs are the most-used collection tools at a crime scene, alternatives are available. These alternatives are reviewed, including their advantages and disadvantages. A critical discussion and conclusions make clear that, unfortunately, neither swabs nor their alternatives are highly effective in recovering DNA from a substrate. Full article

Existing child stature estimation methods have a number of disadvantages. This paper addresses some of these limitations by developing regression-based stature estimation formulae that are more generic and inclusive. A sample of 142 individuals under 12 years of age from the Hamann—Todd Human Osteological Collection and the New Mexico Decedent Images Database were used to generate five least squares linear regression formulae to estimate stature from the diaphyseal length of long bones. All models showed excellent fits to the data (R² close to or at 0.98), and internal validation confirmed the stability and accuracy of model parameters. External validation was performed using a sample of 14 individuals from the Lisbon Collection and the Victoria Institute of Forensic Medicine. Overall, the humerus provides the most accurate estimate of stature, but the femur and tibia showed the greatest coverage. These formulae can be used in a variety of contexts and are not dependent on group affiliation, including sex. Full article

Since the biobanks’ inception in 1980, millions of human biological samples have been stored worldwide for medical research or treatment purposes. Today the secondary use of biobanks plays an increasingly important role in research projects because it allows large-scale research starting from professional collections of biospecimens and related clinical data. It would be limiting, in the “-omics” era, to not consider the enormous potential value to law enforcement of these biospecimens, where the availability of high-performance techniques makes it possible to obtain a large amount of data, even within a single session. Therefore, the quality of the sample, in addition to the associated clinical information, becomes of crucial importance to derive scientifically valid information, including for forensic research purposes. Proposing the introduction of the concept of “solidarity”, traditionally applied only to medical and research biobanks, led to public commitment to forensic medicine. Granting the forensic researcher this possibility certainly raises some questions regarding regulatory and ethical aspects of consent, privacy, confidentiality, transparency, and participant/donor trust. Since the debate has not stopped since the origin of biobanks, this review aims to explore the state of the art relating to the use of human biological material in medical biobanks for biomedical and forensic research. Full article

Adolescents are currently the most digitally connected generation in history. There is an ever-growing need to understand how typical adolescent risk-taking intersects with the vastly criminogenic potential of digital technology. Criminal hacking in older adolescents (16–19-year-olds) was assessed using an adapted Theory of Planned Behaviour (TPB) model, a cohesive theoretical framework that incorporates cognitive processes and human drivers (informed by psychology, cyberpsychology, and criminology theory). In 2021, a large-scale anonymous online survey was conducted across nine European countries. Criminal hacking was assessed using data from 3985 participants (M = 1895, 47.55%; F = 1968, 49.39%). This study formulated a powerful predictive model of youth hacking intention (accounting for 38.8% of the variance) and behaviour (accounting for 33.6% of the variance). A significant minority, approximately one in six (16.34%), were found to have engaged in hacking, and approximately 2% reported engaging in hacking often or very often. Increased age, being male, and offline deviant behaviour were significant predictors of hacking behaviour. In line with the TPB, intention was the strongest individual predictor of hacking behaviour, which in turn was significantly predicted by cognitive processes accounted for by TPB constructs: subjective norms of family and peers, attitudes towards hacking, and perceived behavioural control. These TPB constructs were found to be significantly associated with human factors of risk-taking, toxic online disinhibition, offline deviant behaviour, and demographic variables of age and gender. Implications for future research, interventions, policy, and practice are discussed. Full article

In addition to identifying and prosecuting cyber attackers, attack attribution activities can provide valuable information for guiding defenders’ security procedures and supporting incident response and remediation. However, the technical analysis involved in cyberattack attribution requires skills, experience, access to up-to-date Cyber Threat Intelligence, and significant investigator effort. Attribution results are not always reliable, and skillful attackers often work hard to hide or remove the traces of their operations and to mislead or confuse investigators. In this article, we translate the technical attack attribution problem to the supervised machine learning domain and present a tool designed to support technical attack attribution, implemented as a machine learning model extending the OpenCTI platform. We also discuss the tool’s performance in the investigation of recent cyberattacks, which shows its potential in increasing the effectiveness and efficiency of attribution operations. Full article

Estimating age at death is essential to establish biological profiles from human skeletal remains in both forensic and archeological settings. Imaging studies of skeletal age changes in adults have described the metamorphosis of trabecular bone structure and bone loss in the proximal femur as well as changes in morphology during different stages of life. This study aims to assess the utility of a digital representation of conventional X-ray films of the proximal femur for the estimation of age at death in a sample of 91 adult individuals (47 females and 44 males) of the Coimbra Identified Skeletal Collection. The proposed approach showed a root mean squared error (RMSE) of 17.32 years (and mean absolute error of 13.47 years) for females and an RMSE of 14.06 years (mean absolute error of 11.08 years) for males. The main advantage of this approach is consistency in feature detection and extraction, as X-ray images projected on the femora space will always produce the same set features to be analyzed for age estimation, while more traditional methods rely heavily on operator experience that can lead to inconsistent age estimates among experts. Full article