Binghamton University 3 credits INFO
In large distributed systems, vast quantities of network traffic, system logs, and user activity are continuously produced. Analyzing patterns in this data can reveal anomalies that may indicate cyber-attacks, system failures, or misconfigurations. Increasingly, such analysis forms the foundation of AI-assisted cybersecurity systems that rely on statistical methods, data analytics, and emerging AI techniques to identify unusual behavior and potential threats at scale. The course provides a hands-on approach to applying data analytics methods to securing and maintaining information systems. Potential topics include network traffic analysis, system log monitoring, malware detection, user behavior profiling, threat hunting, data exfiltration detection, and incident response, with emphasis on how data analytics and AI support modern cybersecurity operations. Prerequisites: INFO 501 and INFO 502. Expected to be offered at least once every year. 3 credits.
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