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This paper presents a correction model for malicious, unbalanced parameter false data injection cyber-attacks. Current state-of-art solutions can detect, identify and correct balanced parameter false data injection cyber-attacks. Thus, they consider all the parameters as equal in error, which means the methods will only work when the same percentage attack happens to each parameter. In this paper, a new correction model using a parameter correction Jacobian matrix, τ, and a Taylor series approximation is presented. A framework for measurement gross error analysis is deployed in processing and analyzing cyber-attacks. Chi-square χ² Hypothesis Testing applied to the normalized composed measurement error (CME^N) is considered for cyber-attacks detection, while the largest CME^N error test is used for identification. Validation is performed on the IEEE 14-bus and 118-bus systems. Easy-to-implement model …