By exploiting the communication infrastructure among the sensors, actuators, and control systems, attackers may compromise the security of smart grid systems, with techniques such as Denial of Service (DoS) attack, random attack and data injection attack. In this paper, we present a mathematical model of the system to study these pitfalls and propose a robust security framework for smart grid. Our framework adopts Kalman Filter to estimate the variables of a wide range of state processes in the model. The estimates from the Kalman Filter and the system readings are then fed into the χ 2 -detector or the proposed Euclidean detector. The χ 2 -detector is a proveneffective exploratory method used with Kalman Filter for the measurement of the relationship between dependent variables and a series of predictor variables. The χ 2 -detector can detect system faults/attacks such as DoS attack, short termed and long termed random attacks. However, the study shows that the χ 2detector is unable to detect the statistically derived False Data Injection attack. To overcome this limitation, we prove that Euclidean detector can effectively detect such a sophisticated injection attack.

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