An Early Warning System Against Malicious Activities for Smart Grid Communications
Smart grid presents the largest growth potential in the machine-to-machine market today. Spurred by the recent advances in M2M technologies, the smart meters/sensors used in smart grid are expected not to require human intervention in characterizing power requirements and energy distribution. These numerous sensors are able to report back information such as power consumption and other monitoring signals. However, SG, as it comprises an energy control and distribution system, requires fast response to malicious events such as distributed denial of service attacks against smart meters. In this paper, the authors model the malicious and/or abnormal events, which may compromise the security and privacy of smart grid users, as a Gaussian process.