Distributed Adaptive Push-Button Forensics

Digital Forensics (DF) in distributed environments faces significant challenges, ranging from scalability, complexity, and reliance on traditional DF processes. The problem being addressed in this paper, is the lack of effective automated DF analysis across distributed ecosystems. Inspired by the success of peer-to-peer ($\mathbf{P 2 P}$) architectures, and as a step toward overcoming the limitations of traditional client-server models, a Distributed Adaptive Push-button Forensic (DAPF) System that leverages a decentralized approach is suggested. The DAPF system automates attack data collection and analysis across multiple nodes in an adaptive approach to streamline DF investigations. Preliminary experiments have demonstrated a $\mathbf{3 0 \%}$ reduction in analysis time compared to traditional methods. This work highlights the potential of automation, adaptability, and decentralized architectures in modern DF a step towards distributed digital forensics.