Author(s):
Journal
Institute of Electrical and Electronics Engineers (IEEE)
Abstract
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.
Concluding remarks
In order to provide a complementary mechanism against other measures, context information-based cyber security protection is proposed in this paper. When the protection system detects a fault based on the measurements of a single or couple instrument transformers, the measurements of the whole substation will be collected to carry out pattern classification to validate the fault. A PNN used as pattern classifier has been constructed. The test of real and fake fault exemplars generated with specific rules show that the proposed PNN can identify the fake fault from the real fault with selected smoothing parameters.
Reference details
DOI
10.1109/TPWRD.2006.886775
Resource type
Journal Article
Year of Publication
2007
ISSN Number
0885-8977
Publication Area
Cybersecurity and defense
Date Published
2007-07
How to cite this reference:
Sheng, S., Chan, W. L., Li, K. K., Xianzhong, D., & Xiangjun, Z. (2007). Context Information-Based Cyber Security Defense of Protection System. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/TPWRD.2006.886775 (Original work published)