Sani, Abubakar Sadiq, Yuan, Dong, Mens, Ke and Dong, Zhao Yang (2021) DIACS: A blockchain-based model for systematic data integrity assessment and control. In: 2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT). IEEExplore . Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 1-5. ISBN 9781728188973 ; 9781728188980 ISSN 2167-9665 (Print), 2472-8152 (Online) (doi:https://doi.org/10.1109/ISGT49243.2021.9372235)

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Abstract

As data integrity attacks against smart grid components such as Supervisory Control and Data Acquisition (SCADA) systems mislead system operators into making erroneous decisions, blockchain has emerged as an attractive distributed solution for enabling data integrity due to its transparent and immutability features. Recent studies have shown that a large number of interdependencies between smart grid components hinders the ability of system operators to assess and control the data integrity associated with every component in a secure and timely manner. This paper proposes a new blockchain-based model, known as DIACS, for systematic data integrity assessment and control. DIACS comprises an automated data integrity assessment and control paradigm that uses Fuzzy Cognitive Maps (FCM), and a secure broadcast communication protocol and a system operators support scheme modelled using a Hash-based Broadcast Key Derivation Function (HBKDF) and authenticated encryption to provide security against data integrity attacks, which manipulate smart grid components. We assess risks of data integrity attacks against a SCADA system and highlight aspects relevant to the assessment and control effectiveness of our model.

Item Type:	Conference Proceedings
Title of Proceedings:	2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Uncontrolled Keywords:	smart grid; data integrity assessment and control; blockchain; fuzzy cognitive maps; authenticated encryption
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Internet of Things and Security Research Centre (ISEC) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Related URLs:	Publisher
Last Modified:	09 Nov 2022 10:23
URI:	http://gala.gre.ac.uk/id/eprint/33220

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