Interpolation search-based malicious user detection in smart grids

Abstract

Nowadays energy theft in smart grids has led to severe economic loss to utility companies and countries across the world. Malicious users who illegally steal electricity from the distribution centre without getting noticed lead to unplanned power loss and blackouts in many developing countries. In order to prevent and find the malicious users who steal electricity, a system must be introduced in such a way that the malicious users will be identified easily in a large neighbourhood area network. In this work, to detect energy theft, a decision-making system using the Hadoop multi-cluster model with interpolation search algorithm has been proposed to calculate the actual energy consumed by every user and classify the user as the honest user or malicious user. The proposed interpolation-based approach is lightweight in its operation, which reduces the time complexity for predicting the malicious users in the NAN. The simulation results indicate that the proposed algorithm performs better than the existing approaches in terms of number of inspection steps, execution speed, detection accuracy and false-negative rate.