Adopting social networking concepts in the Internet of Things (IoT) paradigm, establishes a new interesting field called Social Internet of Things (SIoT). Under this, devices socially communicate with each other to solve similar problems using IoT. One of the major areas of such an arena is Smart Grid (SG) power system. SG is an intelligent, efficient but complex Cyber-Physical System (CPS) of the Power Internet of Things (PIOT). The smart grid integrates the power grid (PG) with IOT. Smart Grid (SG) system is operated by its center of control called as the Supervisory Control and Data Acquisition System (SCADA) which has a built-in ICT. SCADA has a State Estimator which screens the real time power states and decides the respective control actions. SG basically facilitates the exchange of 2-way information between the customers and the energy providers through the public IP- based communication protocols. Therefore, the SCADA in SG is highly vulnerable to several cyber-attacks. One such severe threat for the State Estimator in SCADA is the cyber attacks caused by the False Data Injection (FDI). In order to pose a solution for such a challenging attack, this paper introduces a novel scheme for detecting bad data injection in State Estimation. This technique detects both the stealthy and non-stealthy attacks by using the Continuous Prevention and Detection (CPD) algorithm, which does the mechanism of either protecting the SG from attacks in advance or continuously detecting the FDI attacks. The proposed algorithm is initiated by the attack classification which proceeds by the defense mechanisms of the control center in the IOT based electric grid.
Key words: Social Internet of Things; Smart Grid; Cyber-Physical System; Power Internet of Things; Supervisory Control and Data Acquisition System; False Data Injection attack
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