Publication

Abstract : The Deployment of Smart Grid requires consideration of all the security parameters in the entire architecture of Smart Grid. Data Securityand Communication Security are the major milestones in security that need to be addressed in the present scenario in Smart Grid. In thispaper we model a Deep Belief Network to detect the normal and abnormal behaviors in the traffic pattern of Smart Grid data. Deep beliefNetwork has been deployed to identify the anomalies in the Smart Grid data traffic thereby detecting intrusion .Support Vector Machine hasbeen used for intrusion classification after creating the Deep Belief Network Model. Using SVM model with deep belief networks has helpedin reduction of data complexity and also in identifying the core features to be considered for the implementation of Intrusion detection inSmart Grid Model.