Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8648
Title: Context information-based cyber security defense of protection system
Authors: Sheng, S
Chan, WL 
Li, KK
Duan, X
Zeng, X
Keywords: Cyber security
Probabilistic neural networks (PNNs)
Substation automation systems
Issue Date: 2007
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on power delivery, 2007, v. 22, no. 3, p. 1477-1481 How to cite?
Journal: IEEE transactions on power delivery 
Abstract: With the development of a substation automation system, it is now feasible for the intelligent electronic devices-based protection system to collect its measurements from electronic instrument transformers through a communication network such as an Ethernet-based local-area network. The application of a wide-area broadband network in power utilities introduces underlying danger for protection systems to maloperate when receiving fake data packages from an intruder. This paper proposes identifying a vicious fault by using context information, such as voltage and current, of the same substation. When the protection system detects a fault based on measurements transmitted through a network, it collects all measurements of the substation and feeds these data to a probabilistic neural network. Thereafter, the fault caused by fake data that differs from the known fault pattern can be identified and blocked.
URI: http://hdl.handle.net/10397/8648
ISSN: 0885-8977
EISSN: 1937-4208
DOI: 10.1109/TPWRD.2006.886775
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