File Type Identification of File Fragments using Longest Common Subsequence (LCS)
Romi Fadillah Rahmat, Filbert Nicholas, Sarah Purnamawati, Opim Salim Sitompul · Journal of Physics Conference Series · 2017
Computer forensic analyst is a person in charge of investigation and evidence tracking. In certain cases, the file needed to be presented as digital evidence was deleted. It is difficult to reconstruct the file, because it often lost its header and cannot be identified while being restored. Therefore, a method is required for identifying the file type of file fragments. In this research, we propose Longest Common Subsequences that consists of three steps, namely training, testing and validation, to identify the file type from file fragments. From all testing results we can conlude that our proposed method works well and achieves 92.91% of accuracy to identify the file type of file fragment for three data types.