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ArMor: A Data Analytics Scheme to identify malicious behaviors on Blockchain-based Smart Grid System - 2020

Armor: A Data Analytics Scheme To Identify Malicious Behaviors On Blockchain-Based Smart Grid System

Research Area:  Blockchain Technology

Abstract:

The next-generation energy system, i.e., Smart Grid (SG), empowers the real-time transfer of information using advanced metering infrastructure (AMI) and smart meter (SM) between end-consumers and grid. It accelerates various services such as automatic meter reading, time-of-use (TOU) pricing, demand-response management, and many more. Though it has growing security and privacy concerns and the detection of malicious activity is a critical security task that sacrifices the overall Quality-of-Service (QoS) of SG and Quality-of-Experience (QoE) for customers. To address the aforementioned issues, we propose a data analytics Scheme ArMor for malicious activity detection on the blockchain (BC)-based SG system. The ArMor detects data integrity issues in real-time like false data injection attack and SM failure. Here, we proposed a unique ARIMA-based malicious activity detection model and classified the customer. Then, we proposed a Smart Contract (SC)-based incentive mechanism for utility providers handling the malicious activity at their end. It prevents the entry of malicious data into the SG system as transactional data once stored in BC, it is secured using SC. The obtained results are compared against parameters like prediction accuracy, latency, and data storage cost compared to the state-of-the-art approaches to designate the efficacy of the proposed scheme.

Keywords:  

Author(s) Name:  Aparna Kumari; Mohil Maheshkumar Patel; Arpit Shukla; Sudeep Tanwar; Neeraj Kumar; Joel J. P. C. Rodrigues

Journal name:  

Conferrence name:  GLOBECOM 2020 - 2020 IEEE Global Communications Conference

Publisher name:  IEEE

DOI:  10.1109/GLOBECOM42002.2020.9348061

Volume Information: