Quantifying the effects of uncertainty to manage cyber-security risk and enable adaptivity in power grid wide area monitoring and control applications
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The smooth operation of the power grid is based on the effective Wide Area Monitoring and Control systems, which is supposed to provide reliable and secure communication of data. Due to the complexity of the system and inaccuracy of modeling, uncertainty is unavoidable in such systems. So it is of great interest to characterize and quantify the uncertainty properly, which is significant to the functionality of power grid. Trust, as a subjective and expressive concept connoting one party's (the trustor's) reliance on and belief in the performance of another party (the trustee), is modeled to help administrators (trustors) of WAMC systems evaluate the trustworthiness of data sources (trustees), which is essentially a measurement of uncertainty of this system. Both evidence based methods and data based methods are developed to evaluate trustworthiness and describe uncertainty respectively. By modeling both aleatory and epistemic uncertainty with subjective logic and probability distributions respectively, a framework quantifying uncertainty is proposed. Quantification of the uncertainties can greatly help the system administrators to select the most fitting security implementation to achieve both security and QoS with a certain confidence. Based on the quantification framework, an adaptive security mechanism is prototyped, which can adjust the security scheme online according to dynamic requirements and environmental changes, to make the best ongoing trade-off between security assurance and QoS.