Fuzzy rule based classification system from vehicle-to-grid data

Abstract

Vehicle-to-Grid (V2G) system is becoming a very popular concept since it has various benefits such as reducing energy consumption, being environmental friendly, bi-directional charging, and load balancing. Although, it gets highly remarkable and has many advantages, V2G system's security is extremely challenging. Any security flaw in V2G system can cause serious issues on the system. Security issues might open doors to severe damages on the system. One of the most danger damage on such systems is disclosed confidential information. This work therefore analyses what are confidential information features in a V2G system, it then analyses whether a V2G system is vulnerable to attacks or not if the system's confidential information is revealed. To do that, this study used fuzzy-classification technique in which a fuzzy system is developed. It also applied SVM and NB classification techniques in order to compare applied classification techniques in terms of their performances. Comparison results showed that fuzzy-classification technique performed better than other two techniques.