TikTokShop fraud is an emerging challenge in e-commerce investigations, demanding robust digital forensic approaches. This study tackles the complexities of investigating such fraud within the TikTokShop platform, focusing on the acquisition, preservation, and validation of multifaceted digital evidence, including screenshots, payment records, account data, videos, and communication logs. Adhering to ISO/IEC 27037 for evidence handling, Magnet and Oxygen forensic tools were used for systematic evidence acquisition. The analysis using Oxygen Forensic recovered 100% of relevant artifacts, which is slightly higher compared to Magnet Axiom, which recovered 38.46% of artifacts, although both tools were effective in retrieving critical artifacts such as image metadata, account information, and data transfers. Due to image compression by the TikTokShop application, discrepancies in hash values emerged, requiring supplementary validation. Optical Character Recognition (OCR) and Levenshtein distance algorithms quantified textual similarity within image-based evidence, while the Forensically platform enabled advanced image forensic analyses to detect potential tampering and authenticity. This rigorous, multi-layered forensic framework complements traditional hash verification by providing corroborative content-level authentication. Findings confirm that although hash inconsistencies arise from application-induced compression, integrating OCR, Levenshtein, and forensic image analysis enhances the reliability of digital evidence. The novelty of this research lies in its robust synergy of ISO/IEC 27037-compliant handling with advanced digital content verification, contributing to the advancement of digital forensic practices in complex social commerce fraud scenarios.
Alawi et al. (Sat,) studied this question.