Protected bidding against compromised information injection in IoT-based smart grid

Bhuiyan, Md Zakirul Alam and Zaman, M. and Wang, Guojun and Wang, Tian and Rahman, Md. Arafatur and Tao, Hai (2019) Protected bidding against compromised information injection in IoT-based smart grid. In: 2nd EAI International Conference on Smart Grid and Internet of Things, SGIoT 2018, 11 July 2018 , Niagara Falls, Canada. pp. 78-84., 256. ISSN 1867-8211 ISBN 978-303005927-9

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The smart grid is regarded as one of the important application field of the Internet of Things (IoT) composed of embedded sensors, which sense and control the behavior of the energy world. IoT is attractive for features of grid catastrophe prevention and decrease of grid transmission line and reliable load fluctuation control. Automated Demand Response (ADR) in smart grids maintain demand-supply stability and in regulating customer side electric energy charges. An important goal of IoT-based demand-response using IoT is to enable a type of DR approach called automatic demand bidding (ADR-DB). However, compromised information board can be injected into during the DR process that influences the data privacy and security in the ADR-DB bidding process, while protecting privacy oriented consumer data is in the bidding process is must. In this work, we present a bidding approach that is secure and private for incentive-based ADR system. We use cryptography method instead of using any trusted third-party for the security and privacy. We show that proposed ADR bidding are computationally practical through simulations performed in three simulation environments.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Internet of Things (IoT); Smart grids; Demand response; Security attack; Privacy; Compromised information injection
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 24 Oct 2019 03:57
Last Modified: 24 Oct 2019 03:57
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