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Malware Analysis and Intrusion Detection in Cyber-Physical Systems - M. V. Manoj Kumar - Bog

Bag om Malware Analysis and Intrusion Detection in Cyber-Physical Systems

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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781668486665
  • Indbinding:
  • Hardback
  • Sideantal:
  • 456
  • Udgivet:
  • 30. juni 2023
  • Størrelse:
  • 183x29x260 mm.
  • Vægt:
  • 1048 g.
  • 8-11 hverdage.
  • 4. december 2024
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  • BLACK NOVEMBER

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Beskrivelse af Malware Analysis and Intrusion Detection in Cyber-Physical Systems

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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