Development of Forensic Analysis Model for Investigating the Cybercrime Over TOR Network

Abstract-The proliferation of crimes using anonymised networks such as The Onion Router (TOR) has posed considerable hurdles for law enforcement and cybersecurity experts. Conventional forensic methods often have difficulties in tracking illegal activity carried out on TOR because of its encryption and anonymity attributes. This study aims to provide a forensic analysis model tailored for the investigation of criminality inside the TOR network. The model utilises sophisticated data analysis methods, using machine learning classifiers like as Naïve Bayes, Support Vector Machines (SVM), Random Forest, and K-Nearest Neighbours (KNN), to identify anomalous activity and discern attack patterns. Furthermore, it incorporates feature selection techniques to improve classification precision and minimise false positives. The proposed methodology utilises publicly accessible information and network traffic analysis to enhance the detection and investigation of criminality inside the TOR network, providing significant insights for security experts and law enforcement authorities.