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http://dx.doi.org/10.18770/KEPCO.2018.04.02.075

A Security Nonce Generation Algorithm Scheme Research for Improving Data Reliability and Anomaly Pattern Detection of Smart City Platform Data Management  

Lee, Jaekwan (KEPCO Research Institute, Korea Electric Power Corporation)
Shin, Jinho (KEPCO Research Institute, Korea Electric Power Corporation)
Joo, Yongjae (KEPCO Research Institute, Korea Electric Power Corporation)
Noh, Jaekoo (KEPCO Research Institute, Korea Electric Power Corporation)
Kim, Jae Do (KEPCO Research Institute, Korea Electric Power Corporation)
Kim, Yongjoon (KEPCO Research Institute, Korea Electric Power Corporation)
Jung, Namjoon (KEPCO Research Institute, Korea Electric Power Corporation)
Publication Information
KEPCO Journal on Electric Power and Energy / v.4, no.2, 2018 , pp. 75-80 More about this Journal
Abstract
The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.
Keywords
Smart City; Security Platform Module; Key Distribution Center; Random Generation Module;
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  • Reference
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