High precision blood lead radiogenic isotope signatures in a community exposed to Pb contaminated soils and implications for the current Pb exposure of the European population.

Our study provides the most comprehensive dataset for high-precision radiogenic isotopes of lead (Pb) in blood for the western European population. It investigates their potential for elucidating the contribution of soil Pb to blood Pb using a human biomonitoring survey involving 81 adults and 4 children living in the urban area of Liège (Belgium). Soils in the area show moderate (median of 360 mg/kg) to high (95th percentile of 1000 mg/kg) Pb concentrations, due to former metal processing activities. Blood lead levels (BLL) measured in the study population are, on average, quantitatively consistent with a âˆ¼ 20 % increase due to the exposure to Pb from soils, as estimated by a single-compartment biokinetic model. Consistently, its isotopic composition does not represent an endmember that fully accounts for the variability of Blood lead isotope (BLI) compositions measured in the study population. While some individuals show more thorogenic BLI ratios (relatively more enriched in 208Pb), which could be consistent with a greater exposure to local soils and/or by their country of birth, the BLI data mostly follow a trend roughly parallel to the European Standard Lead Pollution (ESLP) line, within the European leaded gasoline field, even two decades after the withdrawal of this source. Differences in BLI are probably associated with factors related to the presence of Pb in dwellings (pipes, paint) and drinking water distribution system, suggesting that the anthropogenic Pb in use, relevant to human exposure, may contain ore components of different origins, including the Australian Pb ore signature.

Analysis of total lip score system and total groove score for gender identification: A cross-sectional study.

Background: Endless ink and pixel space have been spent to validate the use of cheiloscopy classification systems in the field of identification. It is becoming evident that lip-print patterns may provide indications about an individual's gender, race, occupation, habits, blood type, and paternity. Over the course of time, much data have been collected on a substantial population in this field. In the present study, we strive to see how well a noble total lip scoring (TLS) system works in identifying a person's gender among the College of Dentistry students. We also quantified the total groove score (TGS) and compared it with each quadrant for better authentication of the set study design. Materials and Method: A cross-sectional descriptive study was conducted among 60 dental students (30 males and 30 females), with an age range of 18-30 years. Lip prints were recorded using the writing pad method and subsequently digitalized by capturing the images using Adobe Photoshop CS 6 Extended Version, counted and summed up, quadrant-wise, in both upper and lower lips. The TLS and TGS between males and females were statistically calculated using the Jamovi project. Results: The mean value for TLS for males (n = 402; SD ± 92.1) is higher than that for females (n = 348; SD ± 86.1). The correlation matrix applying a non-parametric test for non-continuous data using Spearman's ratio inferred a statistically significant correlation (-0.354) with a P-value of 0.005 for TLS, whereas a correlation (-0.162) of TGS with gender was not so significant with a P-value of 0.217. Conclusion: Our study proved the uniqueness of applying TLS as a novel approach to gender identification. The study revealed that males had a statistically higher lip score than females. Clinical Significance/Future Implications: Being unique, our study inferred the importance of TLS, which needs to be explored in detail for applying, evaluating, and validating its accuracy in forensic research that can help for errorless investigations as full-proof evidence in court.

Relationship between forensic medicine education, stress factors, and mobbing perception from the perspective of specialists in Turkey's universities.

INTRODUCTION: The current situation needs to be presented with scientific data to ensure and improve the quality of specialist training. This study examined the quality of education, instructor competence, stress factors, mobbing, and their interconnections in the domain of forensic medicine specialty education in Turkey. MATERIALS AND METHODS: This cross-sectional study was conducted through an anonymous, web-based survey targeting forensic medicine specialists who have completed their specialist training in university forensic medicine departments within the last three years. The survey consisted of questions regarding issues included in the core education curriculum, educator characteristics, and perceptions of stress and mobbing. Based on the responses provided, the relationships between these factors were statistically analysed. RESULTS: 72.7 % of the study population completed the survey. Nearly half of the participants (46.3 %) did not consider the number of instructors adequate. The quality of instructors (scientific competence, educational and teaching skills, interpersonal relations, accessibility, management, and problem-solving abilities) was determined to be partially sufficient (mean = 3.36). Approximately one-third of the respondents indicated that instructors made the greatest contribution to their specialist training, whereas the proportion of those who said otherwise was much higher. Education received for topics included in the core curriculum was partially sufficient level (mean = 3.04). It was observed that there was a significant relationship between the instructor characteristics, sufficiency score of the taught topics, and perception of mobbing (p < 0.01). The sufficiency scores of instructor characteristics had a 1.02-fold impact on sufficiency ratings of the topics covered in residency training. Among the respondents, 76.9 % reported encountering stress factors during their specialty training, with the most frequently exposed stress factor (52.2 %) being disorganisation within the training program. Among the participants, 22.8 % reported experiencing mobbing. CONCLUSIONS: Education and instructor qualifications were correlated; however, stress factors and mobbing adversely affected education. A close association was observed between education, instructors, stressors, and mobbing. Thus independent and objective auditors tasked with verifying whether institutions meet the established educational standards need to be established.

The invisible evidence: Digital forensics as key to solving crimes in the digital age.

Digital transformation rapidly changes how we live our lives in the post pandemic world. Unfortunately, digital technology is not limited to law abiding organisations and citizens. Criminal organisations and individuals are quick to identify new opportunities with new technologies, and digital transformation is dramatically changing the character of crimes, terror, and other threats. The fast emergence of new crimes is facilitated by possibilities brought by disruptive technologies such as AI, Internet of Things, drones, and cryptocurrencies that can be disastrous tools in the hands of criminals. Consequently, our society needs far better capacity to prevent and investigate criminal acts to protect organisations and citizens. This brings an urgent need to proactively reform digital forensics to significantly increase our capability to meet the strain on society brought by crimes evolving in the digital transformation era. The future of forensic science is already here, characterized by a mix of opportunities and challenges. It is essential to make it harder to effectively use digital technologies for criminal activities, while leveraging the possibilities of digital technologies by those affected, law enforcement agencies, business and organisations. As digital technologies continue to evolve, we need to stay up to date with the latest developments to effectively investigate and prosecute crimes in the digital age. There is an increased reliance on digital evidence, and the amount of heterogeneous digital evidence in criminal cases keep increasing. The forensic science techniques thus become more sophisticated and play an increasingly important role. However, the scientific area is extremely broad, and beyond the capability of most forensic science labs to keep up with the technology forefront development speed. Besides an urgent need to bring up the subject to the political arena, examples of how we can meet the challenges are discussed such as by extending our cooperation, encourage and facilitate cooperation for training and education to handle the extremely broad and rapid development, working out methods for explaining and visualising evidence for the treatment and legal values of digital evidence in prosecution, and cooperation between product developers and crime investigators for swift innovation of digital forensics tools and methodologies for quickly emerging threats. This paper will highlight specific examples where modern digital techniques are used to solve crimes in the physical world as well as crimes committed in the digital domain and discuss how "good AI" can be used to fight "evil AI" and finally touch on the sensitive balance between the increased power of the new digital forensic tools and private integrity.

How Ontologies Have Supported Digital Forensics: Review and Recommendations.

The evolution of digital media has increased the number of crimes committed using digital equipment. This has led to the evolution of the computer forensics area to digital forensics (DF). Such an area aims to analyze information through its main phases of identification, collection, organization, and presentation (reporting). As this area has evolved, many techniques have been developed, mainly focusing on the formalization of terminologies and concepts for providing a common vocabulary comprehension. This has demanded efforts on several initiatives, such as the definition of ontologies, which are a means to identify the main concepts of a given area. Hence, the existing literature provides several ontologies developed for supporting the DF area. Therefore, to identify and analyze the existing ontologies for DF, this paper presents a systematic literature review (SLR) in which primary studies in the literature are studied. This SLR resulted in the identification of ontology building methodologies, ontology types, feasibility points, evaluation/assessment methods, and DF phases and subareas ontologies have supported. These results were based on the analysis of 29 ontologies that aided in answering six research questions. Another contribution of this paper is a set of recommendations on further ontology-based support of DF investigation, which can guide researchers and practitioners in covering existing research gaps.

Mapping consumptions and market size of cocaine, amphetamine and MDMA through wastewater analysis: A Dutch case study.

BACKGROUND AND AIMS: Illicit drug consumption is associated with public health effects and criminal activities. This study aimed to estimate Illicit drug consumption and annual market in the Netherlands from wastewater analysis of drug residues. METHODS: Residues of cocaine, amphetamine and 3,4-methylene dioxymethamphetamine (MDMA) were measured between 2015 and 2022 in 30 Dutch wastewater treatment plants serving both rural and urban populations. These wastewater treatment plants covered 20% of the total Dutch population. The Dutch annual retail market was estimated by extrapolating consumption to the total Dutch population, back-calculating consumption volume, correcting for drug purity and street price collected in voluntary checking services, and accounting for the correlation of consumption and urbanity. RESULTS: The per capita MDMA and cocaine consumption correlated positively with the urbanity of the wastewater treatment plant catchments with r2 of 31% and 64%, respectively. Amphetamine did not show a significant correlation with urbanity. The three studied drugs were conservatively estimated to cover an average annual market value of 903 (95% prediction interval 829 to 987) million Euro for the studied period. Market estimations from prevalence figures and interceptions of international trade were similar. CONCLUSIONS: Illicit drug consumption in the Netherlands appears to correlate positively with urban (in contrast to rural) areas. Wastewater analysis can be used to estimate the volume and monetary value of illicit drug markets as a proof of concept.

Sexual dimorphism and allometry in human scapula shape.

Scapula shape is highly variable across humans and appears to be sexually dimorphic-differing significantly between biological males and females. However, previous investigations of sexual dimorphism in scapula shape have not considered the effects of allometry (the relationship between size and shape). Disentangling allometry from sexual dimorphism is necessary because apparent sex-based differences in shape could be due to inherent differences in body size. This study aimed to investigate sexual dimorphism in scapula shape and examine the role of allometry in sex-based variation. We used three-dimensional geometric morphometrics with Procrustes ANOVA to quantify scapula shape variation associated with sex and size in 125 scapulae. Scapula shape significantly differed between males and females, and males tended to have larger scapulae than females for the same body height. We found that males and females exhibited distinct allometric relationships, and sexually dimorphic shape changes did not align with male- or female-specific allometry. A secondary test revealed that sexual dimorphism in scapula shape persisted between males and females of similar body heights. Overall, our findings indicate that there are sex-based differences in scapula shape that cannot be attributed to size-shape relationships. Our results shed light on the potential role of sexual selection in human shoulder evolution, present new hypotheses for biomechanical differences in shoulder function between sexes, and identify relevant traits for improving sex classification accuracy in forensic analyses.

SentinelFusion based machine learning comprehensive approach for enhanced computer forensics.

In the rapidly evolving landscape of modern technology, the convergence of blockchain innovation and machine learning advancements presents unparalleled opportunities to enhance computer forensics. This study introduces SentinelFusion, an ensemble-based machine learning framework designed to bolster secrecy, privacy, and data integrity within blockchain systems. By integrating cutting-edge blockchain security properties with the predictive capabilities of machine learning, SentinelFusion aims to improve the detection and prevention of security breaches and data tampering. Utilizing a comprehensive blockchain-based dataset of various criminal activities, the framework leverages multiple machine learning models, including support vector machines, K-nearest neighbors, naive Bayes, logistic regression, and decision trees, alongside the novel SentinelFusion ensemble model. Extensive evaluation metrics such as accuracy, precision, recall, and F1 score are used to assess model performance. The results demonstrate that SentinelFusion outperforms individual models, achieving an accuracy, precision, recall, and F1 score of 0.99. This study's findings underscore the potential of combining blockchain technology and machine learning to advance computer forensics, providing valuable insights for practitioners and researchers in the field.

ProcGCN: detecting malicious process in memory based on DGCNN.

The combination of memory forensics and deep learning for malware detection has achieved certain progress, but most existing methods convert process dump to images for classification, which is still based on process byte feature classification. After the malware is loaded into memory, the original byte features will change. Compared with byte features, function call features can represent the behaviors of malware more robustly. Therefore, this article proposes the ProcGCN model, a deep learning model based on DGCNN (Deep Graph Convolutional Neural Network), to detect malicious processes in memory images. First, the process dump is extracted from the whole system memory image; then, the Function Call Graph (FCG) of the process is extracted, and feature vectors for the function node in the FCG are generated based on the word bag model; finally, the FCG is input to the ProcGCN model for classification and detection. Using a public dataset for experiments, the ProcGCN model achieved an accuracy of 98.44% and an F1 score of 0.9828. It shows a better result than the existing deep learning methods based on static features, and its detection speed is faster, which demonstrates the effectiveness of the method based on function call features and graph representation learning in memory forensics.

The role of a digital twin in supporting criminal investigations - a case report about a possible abuse.

As part of a comprehensive analysis, this case report presents a possible case of child maltreatment that can serve as a basis for forensic and medical examiner investigations. This case concerns the death of an infant who was approximately two months old. During a routine examination by the pediatrician at the end of May 2021, the child was found to have a normal head circumference of 31 cm. No other abnormalities were noted. On June 19, 2021, the child died, and an autopsy revealed a head circumference of 44 cm and a subdural hematoma as the cause of death. Questions arose as to who might have abused the child and when. The only evidence was a low-quality cell phone video taken by the child's parents on June 13, 2021, six days before the child's death, in which the child could be seen lying on a pillow. It was necessary to determine whether the child in this video already had an unnatural head circumference. This study presents a novel workflow that demonstrates how to analyze and deal with low quality video to answer questions like the above. The workflow demonstrates the creation of 3D scenes from digital image and video material. These 3D scenes can be used for object measurement and to support forensic and medical investigations. In the present case, where only low quality smartphone images were available, the presented workflow was used to create a 3D scene of the child lying on the pillow. In this 3D scene, it was possible to determine the child's head circumference. These measurements support the findings of the medical examiner (dated June 24, 2021) and confirm the suspicion that possible child abuse had already taken place on June 13, 2021. The innovative approach makes it possible to identify evidence of possible abuse based on a specific point in time, in this case the child's private footage. It also demonstrates the potential of 3D scene reconstruction in complex forensic and medical scenarios.

Contextual bias by Forensic Document Examination trainees: An empirical study from China.

The impact of contextual bias has been repeatedly demonstrated across forensic domains; however, research on this topic in China is scarce. To examine the prevalence of contextual bias in pattern feature-comparison disciplines, we conducted an experiment involving 24 forensic document examination students. The aim was to determine whether knowledge of different contextual information influenced their forensic decision-making. Participants were divided into different context groups and tasked with examining whether questioned signatures with ambiguous features matched reference signatures. The results of independent-samples t-tests for their decision score data in the two context groups exhibited a statistically significant difference (p < 0.05, Cohen's d > 0.8). Moreover, the submitted forensic reports by participants disclosed a biased evaluation of handwriting features. These findings show how contextual information can bias forensic decision-making in handwriting examination. Context management with complementary strategies such as case triage, cognitive training and decision-making transparency must be implemented to minimize bias in handwriting examination.

The forensic potential of environmental DNA (eDNA) in freshwater wildlife crime investigations: From research to application.

Environmental DNA (eDNA) is widely used in biodiversity, conservation, and ecological studies but despite its successes, similar approaches have not yet been regularly applied to assist in wildlife crime investigations. The purpose of this paper is to review current eDNA methods and assess their potential forensic application in freshwater environments considering collection, transport and persistence, analysis, and interpretation, while identifying additional research required to present eDNA evidence in court. An extensive review of the literature suggests that commonly used collection methods can be easily adapted for forensic frameworks providing they address the appropriate investigative questions and take into consideration the uniqueness of the target species, its habitat, and the requirements of the end user. The use of eDNA methods to inform conservationists, monitor biodiversity and impacts of climate change, and detect invasive species and pathogens shows confidence within the scientific community, making the acceptance of these methods by the criminal justice system highly possible. To contextualise the potential application of eDNA on forensic investigations, two test cases are explored involving i) species detection and ii) species localisation. Recommendations for future work within the forensic eDNA discipline include development of suitable standardised collection methods, considered collection strategies, forensically validated assays and publication of procedures and empirical research studies to support implementation within the legal system.

The advent of forensic DNA databases: It's time to agree on some international governance principles!

National forensic DNA databases are a valuable investigative tool, that have the potential to increase the efficacy of criminal investigations. Their unfettered expansion in recent years raises unsettling ethical issues that require close attention. DNA database expansion threatens the rights to privacy, non-discrimination, and equality, and can undermine public trust in government. This perspective piece relies on data from an international mapping study of Forensic DNA Databases to document the expansion of these databases, highlight the ethical issues they raise, and propose key recommendations for more responsible use of this infrastructure.

Social Network Forensics Analysis Model Based on Network Representation Learning.

The rapid evolution of computer technology and social networks has led to massive data generation through interpersonal communications, necessitating improved methods for information mining and relational analysis in areas such as criminal activity. This paper introduces a Social Network Forensic Analysis model that employs network representation learning to identify and analyze key figures within criminal networks, including leadership structures. The model incorporates traditional web forensics and community algorithms, utilizing concepts such as centrality and similarity measures and integrating the Deepwalk, Line, and Node2vec algorithms to map criminal networks into vector spaces. This maintains node features and structural information that are crucial for the relational analysis. The model refines node relationships through modified random walk sampling, using BFS and DFS, and employs a Continuous Bag-of-Words with Hierarchical Softmax for node vectorization, optimizing the value distribution via the Huffman tree. Hierarchical clustering and distance measures (cosine and Euclidean) were used to identify the key nodes and establish a hierarchy of influence. The findings demonstrate the effectiveness of the model in accurately vectorizing nodes, enhancing inter-node relationship precision, and optimizing clustering, thereby advancing the tools for combating complex criminal networks.

Electrochemical classification of benzodiazepines: A comprehensive approach combining insights from voltammetry and liquid chromatography - mass spectrometry.

The growing non-medical use of benzodiazepines (BZs) has led to the emergence of counterfeit BZ pills and new psycho-active substances (NPS) in the BZ class on the illicit market. Comprehensive analytical methods for BZ identification are required to allow law enforcement, first aid responders and drug-checking services to analyze a variety of sample types and contents to make timely decisions on the spot. In this work, the electrochemical behavior of diazepam (DZ), clonazepam (CZ) and alprazolam (AP) is studied on graphite screen-printed electrodes, both with and without dissolved oxygen in the solution, to link their redox signals to their chemical structure. After elucidation of their reduction mechanisms using liquid chromatography coupled to high-resolution mass spectrometry, three structural classes (Class 1, Class 2 and Class 3) were defined, each with different redox centers and electrochemical behavior. Subsequently, 22 confiscated pills containing 14 different BZs were correctly assigned to these three structural classes, with the deoxygenated conditions displaying the highest class selectivity. Finally, the three classes were successfully detected after being spiked into five alcoholic beverages in the context of drug-facilitated sexual assault. For analysis in red wine, which complicated the analysis by interfering with Class 1, a dual test strategy in pH 2 and pH 7 was proposed for accurate detection. Its rapid measurements, broad scope and lack of interference from diluents or colors makes this method a promising approach for aiding various services in combating problematic BZ use.

UGEE-Net: Uncertainty-guided and edge-enhanced network for image splicing localization.

Image splicing, a prevalent method for image tampering, has significantly undermined image authenticity. Existing methods for Image Splicing Localization (ISL) struggle with challenges like limited accuracy and subpar performance when dealing with imperceptible tampering and multiple tampered regions. We introduce an Uncertainty-Guided and Edge-Enhanced Network (UGEE-Net) for ISL to tackle these issues. UGEE-Net consists of two core tasks: uncertainty guidance and edge enhancement. We employ Bayesian learning to model uncertainty maps of tampered regions, directing the model's focus to challenging pixels. Simultaneously, we employ a frequency domain-auxiliary edge enhancement strategy to imbue localization features with global contour information and fine-grained local details. These mechanisms work in parallel, synergistically boosting performance. Additionally, we introduce a cross-level fusion and propagation mechanism that effectively utilizes contextual information for cross-layer feature integration and leverages channel-level correlations for cross-layer feature propagation, gradually enhancing the localization feature's details. Experiment results affirm UGEE-Net's superiority in terms of detection accuracy, robustness, and generalization capabilities. Furthermore, to meet the growing demand for high-quality datasets in image forensics, we present the HTSI12K dataset, which includes 12,000 spliced images with imperceptible tampering traces and diverse categories, rendering it suitable for real-world auxiliary model training.

Brute forcing on secured shell servers emphasising the role of cyber forensics - a quali-quantitative study.

BACKGROUND: Increasing numbers of cyber attacks threaten us personally and professionally. Cyber crimes include obtaining sensitive information (medical or financial) but may extend to organising heinous crimes including murders and aggravated sexual assaults. A major vector of cyber crimes is brute force attacks on secured shell servers. AIM OF STUDY: This research highlights the prevalence of the intensity of brute force attacks on secured shell servers via quali-quantitative analysis of cyber attacks. METHODOLOGY: The brute force attacks were recorded over a period of 20 days with the help of logs taken from five dedicated servers installed in a production environment. RESULTS: There were a minimum of 6470 and maximum of 22,715 attacks on a server per day. The total number of attacks on all the servers during the study period was 1,065,920. The brute force attacks were mainly targeted at the service network accounts. CONCLUSION: Growth of the field of cyber forensics is the optimal solution to prevent the malicious use of internet services and the commissioning of crimes by this means.

Deepfake forensics: a survey of digital forensic methods for multimodal deepfake identification on social media.

The rapid advancement of deepfake technology poses an escalating threat of misinformation and fraud enabled by manipulated media. Despite the risks, a comprehensive understanding of deepfake detection techniques has not materialized. This research tackles this knowledge gap by providing an up-to-date systematic survey of the digital forensic methods used to detect deepfakes. A rigorous methodology is followed, consolidating findings from recent publications on deepfake detection innovation. Prevalent datasets that underpin new techniques are analyzed. The effectiveness and limitations of established and emerging detection approaches across modalities including image, video, text and audio are evaluated. Insights into real-world performance are shared through case studies of high-profile deepfake incidents. Current research limitations around aspects like cross-modality detection are highlighted to inform future work. This timely survey furnishes researchers, practitioners and policymakers with a holistic overview of the state-of-the-art in deepfake detection. It concludes that continuous innovation is imperative to counter the rapidly evolving technological landscape enabling deepfakes.

Scavenger-induced scattering of wild boar carcasses over large distances and its implications for disease management.

Vertebrate scavengers provide essential ecosystem services such as accelerating carrion decomposition by consuming carcasses, exposing tissues to microbial and invertebrate decomposers, and recycling nutrients back into the ecosystem. Some scavengers do not consume carcasses on site but rather scatter their remains in the surroundings, which might have important implications for nutrient transport, forensic investigations and the spread of diseases such as African Swine Fever. However, only a few studies have investigated and measured the scatter distances. Using wild boar (Sus scrofa) carcasses and limbs, we monitored scavenging behavior and measured scatter distances of mammals. We placed 20 carcasses (up to 25 kg) and 21 separate limbs equipped with very high frequency (VHF) transmitters and monitored scavenger activity using camera traps in a mountainous region in southeast Germany. Except for one carcass, all other carcasses and limbs were scattered. We measured 72 scatter distances (of 89 scattering events; mean = 232 m, maximum = 1250 m), of which 75% were dispersed up to 407 m. Scavengers moved scattered pieces into denser vegetation compared to the half-open vegetation at provisioning sites. Red foxes (Vulpes vulpes) were the most common scavenger species, contributing to 72 scattering events (58 measured scatter distances). Our results provide evidence of scatter distances farther than previously assumed and have far-reaching implications for disease management or forensic investigations, as the broader surroundings of carcasses must be included in search efforts to remove infectious material or relevant body parts for forensic analysis.

Pennella balaenoptera actively select injured cetacean skin as attachment sites, making them potentially useful forensic tags.

Cetaceans harbor multiple epibionts on their external surface, and these attach to particular microhabitats. Understanding what drives the selection of attachment sites is relevant for refining the use of epibionts as indicators of their hosts. We report on about 100 females of the mesoparasitic copepod Pennella balaenoptera attached to a dead Cuvier's beaked whale Ziphius cavirostris stranded in Tunisia (western Mediterranean); the first report of P. balaenoptera in this country. The copepods were exclusively attached to numerous incisive, likely anthropogenic, wounds found on the host's skin. This finding suggests that newly recruited females may actively seek skin areas where physical penetration is facilitated; a factor that may help explain patterns of microhabitat selection by Pennella spp., and perhaps other pennellids, on their hosts. The estimated age of parasitization by P. balaenoptera (supported by age estimations of the co-occurring epibiotic barnacle Conchoderma virgatum) also suggests that the cetacean host likely survived these injuries, at least initially, and the presumed cause of death was starvation due to entanglement in a fishing net.