Many static and behavior-based malware detection methods have been
developed to address malware and other cyber threats. Even though
these cybersecurity systems offer good outcomes in a large dataset,
they lack reliability and robustness in terms of detection. There
is a critical need for relevant research on enhancing AI-based
cybersecurity solutions such as malware detection and malicious
behavior identification. Malware Analysis and Intrusion Detection
in Cyber-Physical Systems focuses on dynamic malware analysis and
its time sequence output of observed activity, including advanced
machine learning and AI-based malware detection and categorization
tasks in real time. Covering topics such as intrusion detection
systems, low-cost manufacturing, and surveillance robots, this
premier reference source is essential for cyber security
professionals, computer scientists, students and educators of
higher education, researchers, and academicians.
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