Abstract
Data wiping is used to securely delete securely unwanted files. However, the misuse of data wiping can destroy pieces of evidence to be spoiled in a digital forensic investigation. To cope with the misuse of data wiping, we proposed an anti-anti-forensic method based on NTFS transaction features and a machine learning algorithm. This method allows investigators to obtain information regarding ‘which files are wiped’ and ‘which data wiping tools and data sanitization standards used’. In this study, we achieved good identification of data wiping traces in the NTFS file system. Leveraging the efficiency of machine learning models, our method effectively recognizes wiped partitions and files in the NTFS file system and identifies tools used in data sanitization.
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