Search Results (23)

Sextortion has rapidly expanded into a global cyber-enabled crime that leverages anonymous digital communication and decentralized payment systems. This study examines the financial infrastructures underlying contemporary sextortion by conducting a two-phase analysis of 87 confirmed cases involving cryptocurrency payments. Using blockchain forensic tools and open-source intelligence, the research traces fund movements across perpetrator-controlled wallets, identifies laundering techniques such as mixers, peel-chain transfers, and exchange-based cash-outs, and links these behaviors to narrative patterns within victim reports. The results reveal a dual-tier ecosystem in which mass-produced, multilingual extortion scripts coexist with divergent laundering typologies that differentiate lower-value, high-volume scams from more organized and higher-yield operations. By integrating qualitative and quantitative evidence, this study provides a forensic framework for detecting illicit cryptocurrency activity, improving threat classification, and strengthening investigative and regulatory responses to sextortion and related crypto-enabled interpersonal crimes. Full article

Ensuring strategic resilience in critical infrastructures supported with a machine learning approach requires moving beyond compliance checklists and post-incident analysis toward proactive, intelligence-based approaches. This study introduces the Forensic Resilience Operational Model (FROM), a systems thinking framework designed to embed forensic intelligence into the resilience cycle of complex socio-technical systems. To quantify this integration, the study investigates the determinants of the extent to which four operational pillars (forensic readiness, anomaly detection, governance and privacy safeguards, and structured intelligence integration) affect forensic resilience, using empirical survey data from 212 cybersecurity professionals across critical infrastructure sectors. We deploy Partial Least Squares Structural Equation Modelling (PLS-SEM) to investigate these relationships, and the results confirm that anomaly detection is the strongest contributor to forensic resilience, followed by structured intelligence integration and forensic readiness. Governance safeguards, while comparatively weaker, provide the necessary legitimacy and assurance of compliance. Supported with sector-specific case studies in the maritime, financial, and CERT domains, the findings highlight both the adaptability of the proposed FROM and the operational constraints encountered in real-world contexts. The study contributes to the field of systems-oriented strategic management by demonstrating that, when systematically embedded, forensic intelligence enhances adaptive capacity, supports predictive decision-making, and strengthens resilience in environments characterized by uncertainty and high complexity. Full article

This article examines vulnerability to counterfeit currency fraud in Bulgaria by assessing citizens’ competence in recognizing genuine banknotes of the national currency (BGN) prior to the introduction of euro banknotes in 2026. Counterfeit banknotes represent a form of economic crime in which individual victims’ losses are closely tied to their ability to authenticate cash in everyday transactions. Drawing on level-1 security features and guidelines of the Bulgarian National Bank, we developed a structured questionnaire to operationalize knowledge of key authenticity checks (hologram, intaglio printing, watermark, security thread, see-through register). The survey was administered online and on paper over a 20-day period (22 August–11 September 2025) and completed by 371 respondents from across the country. Using descriptive statistics tools, we identify three distinct groups: (i) highly competent respondents who reliably distinguish genuine from counterfeit banknotes; (ii) individuals with high self-reported confidence but inconsistent performance; and (iii) a particularly vulnerable group with low knowledge of security features, limited awareness of official guidance and low self-confidence. Vulnerability is significantly associated with lower education, residence in smaller settlements, lack of prior exposure to counterfeit banknotes and absence of contact with institutional information campaigns. The findings have direct implications for crime prevention and criminal justice policy: they provide an evidence base for targeted public awareness initiatives and risk-based allocation of resources aimed at protecting high-risk groups from currency-related fraud in the context of the monetary transition. Full article

Corporate fraud remains a persistent problem that highlights the need for improved internal control and governance. Research on corporate governance (CG) and forensic accounting (FA) has been largely performed as separate studies. Little has been done to look at how accountants’ knowledge and the specific training of accountants in fraud awareness for their company’s leaders affect preventing fraud (FP). The study surveyed 150 accountants in India from April 2023 to May 2024. The results are based on Chi-Square testing and binary logistic regression. The study investigated how companies in India incorporate CG policy understanding and FG use for KMP and boards and how these factors affect FP. The findings indicate that understanding CG, using FA, and having specific training on fraud awareness for KMPs and boards of directors are all significant factors in reducing the occurrence of fraud. In addition, general employee training has no impact on FP. The theories of agency, stakeholder, and fraud triangle were combined to create one model to provide guidance to both organizations and regulators on how to institutionalize FG and to improve transparency in governance. Full article

With the rapid advancement of technology in recent years, signatures on contracts and documents have increasingly shifted from traditional handwritten forms on paper to digital handwritten signatures executed on devices (hereafter referred to as digital tablets). This transition introduces new challenges for forensic document examination due to the differences in writing instruments. According to the European Network of Forensic Science Institutes (ENFSI), a Digital Capture Signature (DCS) refers to data points captured during the writing process on digital devices such as tablets, smartphones, or signature pads. In addition to retaining the visual image of the signature, DCS provides more information previously unavailable, including pen pressure, stroke order, and writing speed. These features possess potential forensic value and warrant further study and evaluation. This study employs three devices—Samsung Galaxy Tab S10, Apple iPad Pro, and Apple iPad Mini—together with their respective styluses as experimental tools. Using custom-developed handwriting capture software for both Android and iOS platforms, we simulated signature-writing scenarios common in the financial and insurance industries. Thirty participants were asked to provide samples of horizontal Chinese, English, and number writings (FUJ-IRB NO: C113187), which were subsequently normalized and segmented into characters. For analysis, we adopted distance-based time-series alignment algorithms (FastDTW and SC-DTW) to match writing data across different instances (intra- and inter-writer). The accumulated distances between corresponding data points, such as coordinates and pressure, were used to assess handwriting stability and to study the differences between same-writer and different-writer samples. The findings indicate that preprocessing through character centroid alignment, followed by the analysis, substantially reduces the average accumulated distance of handwriting. This procedure quantifies the stability of an individual’s handwriting and enables differentiation between same-writer and different-writer scenarios based on the distribution of DCS distances. Furthermore, the use of styluses provides more precise distinctions between same- and different-writer samples compared with direct finger-based writing. In the context of rapid advancements in artificial intelligence and emerging technologies, this preliminary study aims to contribute foundational insights into the forensic application of digital signature examination. Full article

The rise in Blockchain-based digital assets has transformed the financial ecosystems, which has also created complex governance and taxation challenges. The pseudonymous and cross-border nature of crypto transactions undermines traditional tax enforcement, leaving regulators such as the South African Revenue Service (SARS) reliant on voluntary disclosures with limited verification mechanisms, while existing Blockchain forensic tools and regulatory technologies (RegTechs) have advanced in anti-money laundering and institutional compliance, their integration into issues related to taxpayer compliance and locally adapted solutions remains underdeveloped. Therefore, this study conducts a state-of-the-art review of Blockchain forensics, RegTech innovations, and crypto tax frameworks to identify gaps in the crypto tax compliance space. Then, this study builds on these insights and proposes a conceptual model that integrates digital forensics, cost basis automation aligned with SARS rules, wallet interaction mapping, and non-fungible tokens (NFTs) as verifiable audit anchors. The contributions of this study are threefold: theoretically, which reconceptualise the adoption of Blockchain forensics as a proactive compliance mechanism; practically, it conceptualises a locally adapted proof-of-concept for diverse transaction types, including DeFi and NFTs; and lastly, innovatively, which introduces NFTs to enhance auditability, trust, and transparency in digital tax compliance. Full article

The article presents a broad and exhaustive approach to financial auditing studies, as well as their current state in academic research. Its main objective is to examine practices in the face of existing challenges. Financial auditing is strongly influenced by international standards, the role of financial auditors in risk management, and the use of new technologies and artificial intelligence. Using a bibliometric analysis of 74 studies extracted from the Scopus database, the authors visualize the evolution of financial auditing using tools such as VOS Viewer. This reveals trends and keywords associated with financial auditing, accounting, management, risk management, and fraud. According to the study, there is a gap in expectations regarding the role of the auditor that is influenced by different cultural contexts and the growing use of forensic accounting services for fraud investigation and detection. The study also highlights the low use of accounting and auditing standards in countries such as Iraq and Egypt and observes the normalization of the fraud trend in Pakistan. Full article

In silico forensic toxicology refers to the emerging application of computational models based on Quantitative Structure–Activity Relationships (QSARs), molecular docking, and predictions regarding Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) as used to predict the toxicological behavior of various substances, particularly in medico-legal contexts. These computational models replicate metabolic pathways, providing insights into the metabolism of substances in the human body, while the results of this approach effectively reflect the necessary compounds, reducing the need for direct laboratory work. This review aims to evaluate whether forensic settings and in silico methods present a cost-effective strategy for investigating unknown substances, aiding in toxicological interpretations, and steering laboratory process analyses. Additionally, financial considerations, such as break-even analysis and Bland–Altman plots, were conducted, indicating that forensic labs conducting over 625 analyses each year can achieve cost efficiency by integrating in silico strategies, thus making them a viable alternative to conventional methods in high-throughput settings. Recent studies have emphasized how machine learning enhances predictive accuracy, thereby boosting forensic toxicology’s capacity to effectively evaluate toxicity endpoints. In silico methods are essential for cases involving novel psychoactive substances (NPSs) or unclear toxicological findings. They are also useful as a supporting method in legal contexts, as they uphold expert testimonies and reinforce evidence claims. The future of forensic toxicology is likely to see the increased implementation of AI-powered techniques, streamlining toxicological investigations and enhancing overall accuracy in forensic evaluations. Full article

The rise in illicit financial activities across the South Africa–Zimbabwe corridor, with an estimated annual loss of $3.1 billion demands advanced AI solutions to augment traditional detection methods. This study introduces FALCON, a groundbreaking hybrid transformer–GNN model that integrates temporal transaction analysis (TimeGAN) and graph-based entity mapping (GraphSAGE) to detect illicit financial flows with unprecedented precision. By leveraging data from South Africa’s FIC, Zimbabwe’s RBZ, and SWIFT, FALCON achieved 98.7%, surpassing Random Forest (72.1%) and human auditors (64.5%), while reducing false positives to 1.2% (AUC-ROC: 0.992). Tested on 1.8 million transactions, including falsified CTRs, STRs, and Ethereum blockchain data, FALCON uncovered $450 million laundered by 23 shell companies with a cross-border detection precision of 94%, directly mitigating illicit financial flows in Southern Africa. For regulators, FALCON met FAFT standards, yielding 92% court admissibility, and its GDPR-compliant design (ε = 1.2 differential privacy) met stringent legal standards. Deployed on AWS Graviton3, FALCON processed 2 million transactions/second at $0.002 per 1000 transactions, demonstrating real-time scalability, making it cost-effective for financial institutions in emerging markets. As the first AI framework tailored for Southern Africa’s financial ecosystems, FALCON sets a new benchmark for ethical AML solutions in emerging economies with immediate applicability to CBDC supervision. The transparent validation of publicly available data underscores its potential to transform global financial crime detection. Full article

Project delays remain a persistent challenge in the construction industry, having significant financial implications and contributing to disputes between project participants. Forensic Delay Analysis (FDA) has emerged as a specialised function that identifies the root causes of such delays, quantifies their duration, and assigns responsibility to the appropriate parties. While FDA is a widely practised process, it has yet to fully exploit the potential of emerging technologies. This study explores the integration of both existing and emerging technologies for enhancing FDA processes. A Design Science Research (DSR) approach is adopted, with data collection methods that involve the use of the literature, archival materials, case studies and survey methods. The research demonstrates how the use of technologies, such as database management systems (DBMSs), building information modelling (BIM), artificial intelligence (AI) and games engines, can improve the analytical efficiency, data management, and presentation of findings through a case study. The study showcases the transformative potential of these interventions in streamlining FDA processes, ultimately leading to more accurate and efficient resolution of construction disputes. The proposed process is exemplified by the development of a prototype: the Forensic Information Modelling Visualiser (FIMViz). The FIMViz is a practical tool that has received positive evaluation by FDA experts. The prototype and the enhanced FDA process model that underpins it demonstrate significant advancement in FDA practices, promoting improved decision-making and collaboration between project participants. Further development is needed, but the results could ultimately streamline the FDA process and minimise the uncertainties in FDA outcomes, thus reducing the incidence of costly disputes to the wider economic benefit of the industry generally. Full article

Forensic medicine has increasingly integrated advanced imaging technologies to improve the accuracy and efficiency of investigations. Techniques such as virtual autopsy, multi-detector computed tomography (MDCT), and artificial intelligence (AI)-driven imaging have revolutionized the identification of injuries and causes of death. Despite these advancements, the field faces operational, ethical, and legal challenges that hinder widespread adoption. Objectives: This systematic review aimed to explore the role of emerging imaging technologies in forensic medicine, identify key challenges in their implementation, and provide insights into optimizing their use in forensic practice, with particular attention to cultural, ethical, and interdisciplinary aspects. Methods: A systematic review was conducted following PRISMA guidelines. Literature searches were performed across six databases, including PubMed, Scopus, Web of Science, and others, focusing on studies discussing imaging technologies in forensic contexts. A total of 10 studies were included after applying eligibility criteria. The data were synthesized using narrative synthesis and thematic analysis. Results: Four key themes emerged: (1) advancements in AI and imaging technologies, (2) operational and financial barriers, (3) ethical and legal considerations, and (4) interdisciplinary collaboration and training. Emerging imaging modalities enhance diagnostic precision and facilitate non-invasive examinations, offering culturally sensitive alternatives to traditional autopsies. However, high costs, algorithmic biases, data security risks, and the lack of standardized forensic imaging protocols present significant challenges. The potential for cross-cultural and international forensic collaborations through AI-enabled imaging was also identified as a promising future direction. Conclusions: Advanced imaging technologies hold transformative potential in forensic medicine. Addressing financial, ethical, and operational challenges through interdisciplinary collaboration, standardized guidelines, and culturally sensitive practices is crucial for maximizing their utility and global acceptance Full article

Background/Objectives: Elder abuse, and more specifically financial exploitation, is expected to be a major problem in modern societies as the worldwide population is getting older. Neuropsychological protocols regarding financial capacity assessment are the only available window allowing us to view the cognitive–emotional–behavioral strengths/deficits and vulnerabilities of individuals. Given the paucity of relevant research in Greece in the most vulnerable individuals such as older adults suffering from neurocognitive disorders (NCDs), this systematic review attempts to investigate whether NCDs impair financial capacity and to highlight the most important factors that can predict financial incapacity in Greek older patients and the likelihood of financial abuse. Methods: A systematic search was conducted in Embase, PsycINFO, and PubMed. Results: The search identified n = 21 relevant research articles. The synthesis of available evidence supports that financial incapacity is clearly demonstrated in the group of Greek older adults suffering from NCDs of different severity and etiology; thus, such changes can assist diagnosis, treatment, and care of these individuals, but the implications for elder abuse in the Greek cultural context have not been examined in detail so far. Conclusions: Given the unique source of information that neuropsychological assessments represent by revealing the importance of factors such as arithmetic cognition and relevant brain volume changes in the left angular gyrus, depressive mood, apathy, frailty, vascular risk factors, and financial illiteracy, forensic neuropsychology can play a vital role in protecting older individuals from financial abuse. Full article

This study examines some of the documentation tools and techniques that forensic accountants, internal auditors, external auditors, and others can use to document accounting and financial reporting systems under investigation. While prior research has addressed these items piecemeal, this study is the first to incorporate them, along with current related research and theoretical foundation, and relate them in aggregate to the work of forensic accountants, internal auditors, external auditors, and others. Inputs, processes, and outputs of modern accounting and financial reporting systems are often difficult to fully grasp, with weaknesses obscured by the complexities of the system. These weaknesses make a system vulnerable to fraudsters, embezzlers, hackers, and others who will take advantage of system weaknesses to perpetrate financial fraud, embezzlement, or other financial crimes. Documentation tools and techniques examined in this study will be useful to forensic accountants, internal auditors, external auditors, and others for identifying the components, processes, and potential weaknesses of accounting and financial reporting systems. Full article

Third molar extraction is the most common procedure in oral and maxillofacial surgery. Third molars are considered less functional than other teeth and are often extracted. Sometimes, they are also used for auto-transplantation for the benefit of oral rehabilitation. Since many biological factors are involved in this surgical approach, herein, we outline a review of the biological characteristics of medico-legal/forensic interest, in addition to presenting a successful clinical case. A scoping review of currently available research data (following the principles of PRISMA-ScR or the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) on third molar auto-transplantation was conducted by drawing upon the main databases (Scopus, PubMed, Google Scholar and LILACS) to evaluate biological and clinical characteristics possibly relatable to forensic issues. All the collected data were summarized and elaborated on for the purpose of this article. A patient underwent extraction of the right upper first molar and auto-transplantation of the unerupted ipsilateral third molar. Many biologic and clinical factors are involved in the success of this clinical procedure. Knowledge of third molar anatomy, of its development and viable surgical approaches are all essential elements; just as important are the treatment of the tooth before and after transplantation and the integrity of the periodontal ligament. Follow-up of the clinical case for 5 years made it possible to verify the stability of the procedure over time. Third molar auto-transplantation is feasible and cost-effective. However, the use of third molars as donor teeth in auto-transplantation may have medico-legal implications. The lack of official protocols and consistent evidence-based guidelines for operators still prevent such a procedure from becoming mainstream; therefore, it is viewed with suspicion by clinicians and patients, even though the biological factors herein detected point to a reasonably high degree of safety. The understanding of many specific biological and clinical factors involved in the stability of third molar auto-transplantation allows for a thorough understanding of the forensic implications relevant to clinical practice. Effective communication and information provision are therefore of utmost importance, in the interest of both patients and doctors. Full article

Cloud computing technology is rapidly becoming ubiquitous and indispensable. However, its widespread adoption also exposes organizations and individuals to a broad spectrum of potential threats. Despite the multiple advantages the cloud offers, organizations remain cautious about migrating their data and applications to the cloud due to fears of data breaches and security compromises. In light of these concerns, this study has conducted an in-depth examination of a variety of articles to enhance the comprehension of the challenges related to safeguarding and fortifying data within the cloud environment. Furthermore, the research has scrutinized several well-documented data breaches, analyzing the financial consequences they inflicted. Additionally, it scrutinizes the distinctions between conventional digital forensics and the forensic procedures specific to cloud computing. As a result of this investigation, the study has concluded by proposing potential opportunities for further research in this critical domain. By doing so, it contributes to our collective understanding of the complex panorama of cloud data protection and security, while acknowledging the evolving nature of technology and the need for ongoing exploration and innovation in this field. This study also helps in understanding the compound annual growth rate (CAGR) of cloud digital forensics, which is found to be quite high at ≈16.53% from 2023 to 2031. Moreover, its market is expected to reach ≈USD 36.9 billion by the year 2031; presently, it is ≈USD 11.21 billion, which shows that there are great opportunities for investment in this area. This study also strategically addresses emerging challenges in cloud digital forensics, providing a comprehensive approach to navigating and overcoming the complexities associated with the evolving landscape of cloud computing. Full article