Lost Data Retrieval Lab: A Safe and Reproducible Workflow for Simulated File Recovery and SHA-256 Integrity Verification
Abstract
Lost Data Retrieval Lab is a Python-based educational application designed to demonstrate simulated file recovery, digital evidence documentation, and data integrity verification. Built with Python, Streamlit, and Pandas, the application generates synthetic test files, records SHA-256 hashes, simulates accidental deletion, creates recovery copies, and verifies file integrity against an original manifest. It also provides an interactive dashboard, activity logs, recovery analytics, and downloadable JSON case reports. I developed this project to explore practical digital forensics concepts, safe file handling, cryptographic hashing, and reproducible cybersecurity workflows. The project reflects my interest in applying programming to cybersecurity challenges while strengthening my skills in software development, data integrity, and technical research. Important limitation: The current version simulates deletion by moving files between folders. It is an educational prototype, not a tool for recovering permanently deleted data from physical storage devices.
