MAHIVE: Modular Analysis Hierarchical Intrusion Detection System Visualization Event Cybersecurity Engine for Cyber-Physical Systems and Internet of Things Devices
MAHIVE: Modular Analysis Hierarchical Intrusion Detection System Visualization Event Cybersecurity Engine for Cyber-Physical Systems and Internet of Things Devices
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Date
2021-01-05
Authors
Steiner, Stuart
Oyewumi, Ibukun
Conte De Leon, Daniel
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7100
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Abstract
Cyber-Physical Systems (CPS), including Industrial Control Systems (ICS) and Industrial Internet of Things (IIoT) networks, have become critical to our national infrastructure. The increased occurrence of cyber-attacks on these systems and the potential for catastrophic losses illustrates the critical need to ensure our CPS and ICS are properly monitored and secured with a multi-pronged approach of prevention, detection, deterrence, and recovery. Traditional Intrusion Detection Systems (IDS) and Intrusion Detection and Prevention Systems (IDPS) lack features that would make them well-suited for CPS and ICS environments. We report on the initial results for MAHIVE: Modular Analysis Hierarchical IDS Visualization Event cybersecurity engine. MAHIVE differs from traditional IDS in that it was specifically designed and developed for CPS, ICS, a IIoT systems and networks. We describe the MAHIVE architecture, the design, and the results of our evaluation using two ICS testbed penetration testing experiments.
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Internet of Things Security: CyberAssurance for Edge, Software Defined, and Fog Computing Systems,
cyber physical systems cybersecurity,
distributed intrusion detection,
semantic stream processing
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9 pages
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Proceedings of the 54th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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