Advancing Digital Forensic Intelligence
S. Niveditha, S Shreyanth, R. Delshi Howsalya Devi, R. Sarveshwaran, P. K. Rajesh · 2024
As the threat landscape evolves and cyber-attacks get more complex, traditional approaches to digital forensics are becoming useless. This study&s;s research focuses on the use of EdgeAI techniques to advance digital forensic intelligence (DFI). EdgeAI is a hybrid of edge computing and AI algorithms that enables real-time analysis, proactive incident response, and increased decision-making skills. The need of employing EdgeAI techniques to overcome the limits of standard forensic procedures is emphasized in the chapter. Edge computing allows scientists to process and analyse data at the network edge, dramatically lowering response times and improving scalability and responsiveness. AI algorithm integration provides predictive modelling, anomaly detection, and complicated pattern recognition, providing investigators with proactive threat detection capabilities. The chapter also delves into the technical components of EdgeAI-enabled data capture and analysis, EdgeAI-driven incident response and investigation, and EdgeAI-enhanced threat intelligence and detection. To obtain predictive DFI, machine learning algorithms and deep learning architectures are used, boosting enquiry efficiency and efficacy. Furthermore, it highlights the capacity of EdgeAI techniques to deal with the exponential growth of data amounts while overcoming the restrictions associated with traditional forensic procedures. The collected results indicate the EdgeAI integration&s;s substantial values. EdgeAI approaches result in increased scalability, shorter response times, and higher event detection rates. The numerical findings show an increase in accuracy to 94.5%, precision to 91.2%, recall to 87.8%, F1 score to 89.5%, and detection rate to 96.3%. Real-time threat detection and proactive investigation enable rapid cyber threat mitigation, reducing financial and operational risks. The EdgeAI architecture protects privacy by storing data locally, lowering the danger of unauthorized access. By utilizing EdgeAI approaches, organizations can improve scalability, minimize network congestion, boost data processing capabilities, and improve the efficiency and effectiveness of digital forensic investigations, allowing for a faster response time to cyber disasters.