Image processing and machine learning for data investigation in flash memory - Chew, Wei Min (Nanyang Technological University, 2023)
As the world's data continues to grow, memory storage is essential for retaining and accessing information. Flash memory, a type of non-volatile storage, is used for permanent data storage. However, data security is of great concern due to the potential for data loss through deletion, encryption, or corruption. Digital forensics is an important tool for analyzing and preserving digital evidence in the event of a cyberattack or data breach. This project focuses on investigating data stored in flash memory of unfunctional electronic devices using image processing and machine learning techniques. The report includes a literature review of image processing, machine learning, as well as a detailed methodology on segmentation using U-Net, designing a localization algorithm, and using LeNet-5 for classification of data in flash memory into binaries 1’s and 0’s. Experimental results are presented and discussed, and recommendations for future work are provided.