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The Design and Classification of Cheating Attacks on Power Marketing Schemes in Resource Constrained Smart Micro-Grids

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Smart Micro-Grid Systems Security and Privacy

Part of the book series: Advances in Information Security ((ADIS,volume 71))

Abstract

In this chapter, we provide a framework to specify how cheating attacks can be conducted successfully on power marketing schemes in resource constrained smart micro-grids. This is an important problem because such cheating attacks can destabilise and in the worst case result in a breakdown of the micro-grid. We consider three aspects, in relation to modelling cheating attacks on power auctioning schemes. First, we aim to specify exactly how in spite of the resource constrained character of the micro-grid, cheating can be conducted successfully. Second, we consider how mitigations can be modelled to prevent cheating, and third, we discuss methods of maintaining grid stability and reliability even in the presence of cheating attacks. We use an Automated-Cheating-Attack (ACA) conception to build a taxonomy of cheating attacks based on the idea of adversarial acquisition of surplus energy. Adversarial acquisitions of surplus energy allow malicious users to pay less for access to more power than the quota allowed for the price paid. The impact on honest users, is the lack of an adequate supply of energy to meet power demand requests. We conclude with a discussion of the performance overhead of provoking, detecting, and mitigating such attacks efficiently.

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Notes

  1. 1.

    Also referred to as a bargaining agents by Priest and Tol [15].

  2. 2.

    Also referred to as bargaining agent by Priest and Tol [15].

  3. 3.

    The domain is considered abstract as its elements do not have the specifics required for the modelling and analysis of a CDA.

  4. 4.

    These are described as disclosure resources.

  5. 5.

    Strategy developed by Tesauro and Bredin [29] as a modification of the Gjerstad-Dickhaut (GD) strategy that uses dynamic programming to price orders.

  6. 6.

    Aggressive behaving agents focus on successfully bidding while trading off their profitability.

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Acknowledgements

This work is part of the joint SANCOOP programme of the Norwegian Research Council and the South African National Research Foundation under NRF grant 237817; funded by Hasso-Plattner-Institute at UCT; and UCT postgraduate funding.

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Authors and Affiliations

  1. Department of Computer Science, University of Cape Town, Cape Town, South Africa

    Anesu M.  C. Marufu

  2. Hasso-Plattner-Institute, Faculty of Digital Engineering, University of Potsdam, Potsdam, Germany

    Anne V. D. M. Kayem

  3. Department of Mathematics and Information Security, Royal Holloway, University of London, Egham, Surrey, UK

    Stephen D. Wolthusen

  4. Norwegian Information Security Laboratory, Gjovik University College, Norwegian University of Science and Technology, Trondheim, Norway

    Stephen D. Wolthusen

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  1. Anesu M.  C. Marufu
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Correspondence to Anesu M.  C. Marufu .

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Editors and Affiliations

  1. Hasso-Plattner-Institute, Faculty of Digital Engineering, University of Potsdam, Potsdam, Germany

    Anne V. D. M. Kayem

  2. Department of Mathematics and Information Security, Royal Holloway, University of London, Egham, Surrey, UK

    Stephen D. Wolthusen

  3. Hasso-Plattner-Institute, Faculty of Digital Engineering, University of Potsdam, Potsdam, Germany

    Christoph Meinel

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Marufu, A.M. ., Kayem, A.V.D.M., Wolthusen, S.D. (2018). The Design and Classification of Cheating Attacks on Power Marketing Schemes in Resource Constrained Smart Micro-Grids. In: Kayem, A., Wolthusen, S., Meinel, C. (eds) Smart Micro-Grid Systems Security and Privacy. Advances in Information Security, vol 71. Springer, Cham. https://doi.org/10.1007/978-3-319-91427-5_6

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