NDLI: UC Davis UC Davis Previously Published Works Title Hybrid Control Network Intrusion Detection Systems for Automated Power Distribution Systems

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UC Davis UC Davis Previously Published Works Title Hybrid Control Network Intrusion Detection Systems for Automated Power Distribution Systems

Content Provider	Semantic Scholar
Author	Tockman, Melvyn S. Erozan, S. Gupta, Prabodh Piantadosi, Steven Mulshine, James L. Ruckdeschel, John C.
Copyright Year	2007
Abstract	In this paper, we describe our novel use of network intrusion detection systems (NIDS) for protecting automated distribution systems (ADS) against certain types of cyber attacks in a new way. The novelty consists of using the hybrid control environment rules and model as the baseline for what is normal and what is an anomaly, tailoring the security policies to the physical operation of the system. NIDS sensors in our architecture continuously analyze traffic in the communication medium that comes from embedded controllers, checking if the data and commands exchanged conform to the expected structure of the controllers interactions, and evolution of the system's physical state. Considering its importance in future ADSs, we chose the fault location, isolation and service restoration (FLISR) process as our distribution automation case study for the NIDS deployment. To test our scheme, we emulated the FLISR process using real programmable logic controllers (PLCs) that interact with a simulated physical infrastructure. We used this testbed to examine the capability of our NIDS approach in several attack scenarios. The experimental analysis reveals that our approach is capable of detecting various attacks scenarios including the attacks initiated within the trusted perimeter of the automation network by attackers that have complete knowledge about the communication information exchanged.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://escholarship.org/content/qt1q63z548/qt1q63z548.pdf
Alternate Webpage(s)	https://escholarship.org/content/qt7v04106q/qt7v04106q.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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