Mobile Forensic Investigation of E-Commerce Fraud Using DFRWS Method and Perceptual Hashing - Rizal Prambudi; Imam Riadi; Murinto Murinto (JUITA: Jurnal Informatika, 2026)
Social media platforms have enabled real-time communication and broad user interaction, but they are often exploited for cybercrime. One such vulnerable medium is e-commerce applications, which facilitate transactions and store sensitive user data. This study investigates digital evidence in a simulated fraud case involving an e-commerce application by applying mobile forensic techniques guided by the Digital Forensic Research Workshop framework. The investigation focused on recovering user accounts, text messages, images, and videos from an Android smartphone. Two forensic tools Oxygen Forensic Detective and MOBILedit Forensic Express were used for data extraction and analysis. To improve the reliability of visual evidence, the study incorporated perceptual hashing and wavelet hashing techniques to validate compressed image files. The results showed that Oxygen Forensic Detective recovered 71.4% of digital evidence, while MOBILedit achieved 57%. Although both tools successfully recovered multimedia files, Oxygen performed better in extracting text messages. These findings demonstrate the effectiveness of mobile forensic methods in identifying and validating digital evidence in e-commerce fraud cases. Moreover, integrating the DFRWS methodology with perceptual hashing significantly improves the interpretation of manipulated or compressed images, thus enhancing the evidentiary value for legal proceedings.