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Contextual Dishonest Behaviour Detection for Cognitive Adaptive Charging in Dynamic Smart Micro-Grids

Radenkovic, Milena; Walker, Adam

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Authors

ADAM WALKER Adam.WalkerEEE@nottingham.ac.uk
Assistant Professor



Abstract

The emerging Smart Grid (SG) paradigm promises to address decreasing grid stability from thinning safe operating margins, meet continually rising demand from pervasive high capacity devices such as electric vehicles (EVs), and fully embrace the shift towards green energy solutions. At the SG edge, widespread decentralisation of heterogeneous devices coupled with fluctuating energy availability and need as well as a greatly increased fluidity between their roles as energy producers, consumers, and stores raises significant challenges to ensuring robustness and security of both information and energy exchange. Detecting and mitigating both malicious and non-malicious threats in these environments is essential to the realisation of the full potential of the SG. To address this need for robust, localised, real-time security at the grid edge we propose CONCEDE, a collaborative cross-layer ego-network integrity awareness and attack impact reduction extension to our previous work on delay-tolerant cognitive adaptive energy exchange. We detail a substantial, targeted, energy disruption attack perpetrated by colluding mobile energy prosumers. Our CONCEDE proposal is then evaluated in multiple, diverse smart micro-grid (SMG) scenarios using hybrid traces of EVs and infrastructure from Europe, North America, and South America in the presence of a coordinated attack from malicious distributors seeking to disrupt energy supply to a target community. We show that CONCEDE successfully detects and identifies the nodes exhibiting malicious, dishonest behaviour and that CONCEDE also reduces the impact of a coordinated energy disruption attack on innocent parties in all explored scenarios across multiple criteria.

Citation

Radenkovic, M., & Walker, A. (2019). Contextual Dishonest Behaviour Detection for Cognitive Adaptive Charging in Dynamic Smart Micro-Grids. In Proceedings on 2019 15th Annual Conference on Wireless On-demand Network Systems and Services (WONS) (44-51). https://doi.org/10.23919/WONS.2019.8795461

Conference Name IEEE/IFIP WONS 2019 15th Annual Conference 2019 15th Annual Conference on Wireless On-demand Network Systems and Services (WONS)
Conference Location Wengen, Switzerland
Start Date Jan 22, 2019
End Date Jan 24, 2019
Acceptance Date Dec 14, 2018
Online Publication Date Aug 15, 2019
Publication Date 2019
Deposit Date Jan 15, 2019
Publicly Available Date Jan 15, 2019
Publisher Institute of Electrical and Electronics Engineers
Pages 44-51
Book Title Proceedings on 2019 15th Annual Conference on Wireless On-demand Network Systems and Services (WONS)
ISBN 978-1-5386-8192-3
DOI https://doi.org/10.23919/WONS.2019.8795461
Keywords Smart energy; Mobile DTNs; Autonomous Vehicles; Security
Public URL https://nottingham-repository.worktribe.com/output/1429610
Publisher URL https://ieeexplore.ieee.org/document/8795461

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ZIP compressed plain text archive, containing: Data: Comma Separated Variables [.csv], Text [.txt] and Well-known text [.wkt] files; Programming Code: Java [.java] and Python [.py] (1.3 Mb)
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