A detection model for anomalies in smart grid with sensor network

Abstract

In this paper, we present a model to monitor the smart grid for any anomalous/malicious activity or attack. The model uses machine learning techniques to detect and classify anomalies from the sensory observations. It is helpful for ensuring the security and stability of the smart grid. The model relies on the real time data collected using wireless sensor… (More)

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