Correlation analysis of pilots and drones using DJI cloud forensic data

This study examines psychopathy and aggression profiles in offenders with Antisocial Personality Disorder (ASPD) using standardized forensic assessment tools. It hypothesizes that higher psychopathy scores (PCL-R) will be significantly associated with greater aggression, providing insights for forensic risk evaluation and management. The study included incarcerated offenders evaluated at the Council of Forensic Medicine between 2014 and 2024 who were diagnosed with ASPD according to DSM-5 criteria. Participants voluntarily completed standardized assessments including the Psychopathy Checklist–Revised (PCL-R), Buss–Perry Aggression Questionnaire (BPAQ), Beck Depression and Anxiety Inventories, and the Interpersonal Cognitive Distortions Scale. Sociodemographic, clinical, and forensic data were collected through a semi-structured interview form and official court records. Group comparisons and correlation analyses were performed, with statistical significance set at p < 0.05. Among offenders with ASPD, violent offenders were more frequently unemployed (58.8%) and divorced (45.1%) compared to sexual offenders (31.6% and 18.4%, respectively; p = 0.009 and p = 0.022). Substance use (84.3% vs. 44.7%; p < 0.001), non-suicidal self-injury (86.3% vs. 28.9%; p < 0.001), and physical abuse (88.2% vs. 44.7%; p < 0.001) were markedly higher in the violent group, while sexual offenders more often reported sexual abuse (52.6%; p < 0.001). Psychopathy scores were significantly higher in violent offenders (Mean = 28.0 ± 5.8) than sexual offenders (Mean = 11.9 ± 3.7; p < 0.001), whereas depression scores were greater in sexual offenders (Mean = 35.2 ± 8.1 vs. 13.6 ± 5.3; p < 0.001). Logistic regression identified psychopathy as the strongest predictor of violent offending (β = 0.60, p < 0.001, OR = 1.82), explaining 83% of variance (Nagelkerke R² = 0.83). Violent and sexual offenders with ASPD exhibited distinct profiles, with psychopathy strongly associated with violent offending and internalizing symptoms and sexual trauma linked to sexual crimes. These findings emphasize the need for individualized, mechanism-based forensic interventions and risk assessments focusing on psychopathy and cognitive factors.

Advanced digital forensics technologies provide powerful basis in criminal investigation. Due to the complexity and diversity of data as well as the increasing quantity of the data, traditional digital forensics technologies have already can not adapt to the analysis requirements. This paper provides a visualization approach to analyze multiple types of data for digital forensics which provide users three interrelated tools: the RadViz tool, the PMViz tool and the SGGViz tool. Our solution focuses on the correlation analysis of trajectories and transactions, and it plays an important role in the process of analyzing the case in VAST 2014 Mini-challenge 2.

The purpose of this study is to investigate the impact of forensic accounting on the ethical financial practices of Nepalese organizations. The predictor variables are litigation support services, forensic data analysis, and ethical awareness, while the outcome variable of the study is ethical financial practices. This research employed a descriptive and causal relational research design to test the hypotheses. The population of the study consisted of respondents from the financial sector in Kathmandu. A total of 434 structured questionnaires were distributed as the primary data source, and 276 (63.59 percent) useful responses were received. The research adopted a purposive sampling technique for cross-sectional data collection. The study utilized descriptive statistics, correlation, and regression analysis, including Cronbach’s alpha, for data analysis. The findings revealed a positive association between litigation support services and ethical financial practices (r = 0.501, p &lt; 0.05). Similarly, a strong positive and significant relationship was found between forensic data analysis and ethical financial practices (r = 0.704, p &lt; 0.05). Additionally, a strong positive association was identified between ethical awareness and ethical financial practices (r = 0.611, p &lt; 0.05). The results of this study can contribute to existing literature and serve as evidence for organizations, professionals, policymakers, practitioners, and other stakeholders.

Digital forensic data from volatile system memory possesses the following distinctive features: volatility, transience, phased stability, complexity, relevance of collected data, and phased behavior predictability. We present a computer forensic analysis model (CERM) for the reconstruction of a chain of evidence of volatile memory data. CERM frees analysts from being confined to the traditional analysis approach of digital forensic data that requires single evidence-oriented analysis. In CERM, they can focus on higher abstract levels involving the relationships of independent pieces of evidence and analyze patterns to construct a chain of evidence from the perspective of Evidence Law. In addition to CERM, we have designed a correlation analysis algorithm based on time series. Experimental tests have been conducted to verify the established model and designed algorithm. The experimental result shows that CERM is feasible and efficient, thus providing a new analysis perspective for digital forensic data from volatile system memory.