A Framework to Automate the Digital Forensics Pipeline of Electron-based Social Media Applications

Social media applications have become essential tools for communication, encouraging global interaction while simultaneously presenting opportunities for criminal activities. With the rise of Electron-based social media platforms, such as Discord, Slack, and WhatsApp, digital forensic investigators face challenges in extracting and analyzing digital artifacts due to data heterogeneity and sheer volume. This research introduces an automated framework designed to streamline the forensic analysis pipeline for Electron-based applications. The framework identifies, collects, standardizes, and processes artifacts from mul-tiple storage locations, leveraging advanced Natural Language Processing (NLP) techniques to filter relevant data and generate seamless reports. This framework enhances the efficiency and accuracy of digital forensic investigations.