Network Forensics and Incident Response Tool with AI-Assisted Threat Analysis

This research aims at the creation of an enhanced Network Forensics and Incident Response Tool, making use of AIbased threat analysis to enhance network security. The tool is engineered to offer real-time monitoring, detection, and response features that allow for the identification of prospective security incidents. Through the inspection of network traffic via packet capture (PCAP) files, AI algorithms learn to identify anomalies and suspicious activity patterns that reflect cyber threats. The incorporation of AI dramatically enhances the accuracy of threat-detection, minimizes false positives, and maximizes operational efficiency. Moreover, the software includes automated email notifications to instantly alert security teams of identified incidents, facilitating quick response and mitigation. The study emphasizes the imperative of merging machine learning with network forensics to develop a holistic security incident management approach. The tool's flexibility ensures that it is well-suited to various network infrastructures, providing an anticipatory solution for protection against constantly changing cyber threats. This research highlights the role of AI-based tools in contemporary cybersecurity systems, calling attention to their ability to revolutionize threat response and detection.