The Internet of Things forensics is a specialised field within digital forensics that focuses on the identification of security incidents, as well as the collection and analysis of evidence with the aim of preventing future attacks on IoT networks. IoT forensics differs from other digital forensic fields due to the unique characteristics of IoT devices, such as limited processing power and connectivity. Although numerous studies are available on IoT forensics, the field is rapidly evolving, and comprehensive surveys are needed to keep up with new developments, emerging threats, and evolving best practices. In this respect, this paper aims to review the state of the art in IoT forensics and discuss the challenges in current investigation techniques. A qualitative analysis of related reviews in the field of IoT forensics has been conducted, identifying key issues and assessing primary obstacles. Despite the variety of topics and approaches, common issues emerge. The majority of these issues are related to the collection and pre-processing of evidence because of the counter-analysis techniques and challenges associated with gathering data from devices and the cloud. Our analysis extends beyond technological problems; it further identifies the procedural problems with preparedness, reporting, and presentation as well as ethical issues. In particular, it provides insights into emerging threats and challenges in IoT forensics, increases awareness and understanding of the importance of IoT forensics in preventing cybercrimes, and ensures the security and privacy of IoT devices and networks. Our findings make a substantial contribution to the field of IoT forensics, as they not only involve a critical analysis of the challenges presented in existing works but also identify numerous problems. These insights will greatly assist researchers in identifying appropriate directions for their future research.

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.

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.

BACKGROUND: 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.
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 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.

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.

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.

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.

Combating wildlife crimes in South Africa requires accurate identification of traded species and their products. Diagnostic morphological characteristics needed to identify species are often lost when specimens are processed and customs officials lack the expertise to identify species. As a potential solution, DNA barcoding can be used to identify morphologically indistinguishable specimens in forensic cases. However, barcoding is hindered by the reliance on comprehensive, validated DNA barcode reference databases, which are currently limited. To overcome this limitation, we constructed a barcode library of cytochrome c oxidase subunit 1 and cytochrome b sequences for threatened and protected mammals exploited in southern Africa. Additionally, we included closely related or morphologically similar species and assessed the database\'s ability to identify species accurately. Published southern African sequences were incorporated to estimate intraspecific and interspecific variation. Neighbor-joining trees successfully discriminated 94%-95% of the taxa. However, some widespread species exhibited high intraspecific distances (>2%), suggesting geographic sub-structuring or cryptic speciation. Lack of reliable published data prevented the unambiguous discrimination of certain species. This study highlights the efficacy of DNA barcoding in species identification, particularly for forensic applications. It also highlights the need for a taxonomic re-evaluation of certain widespread species and challenging genera.

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.