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Incentive-driven attacker for corrupting two-party protocols

Lookup NU author(s): Roberto Metere

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2018 The Author(s) Adversaries in two-party computation may sabotage a protocol, leading to possible collapse of the information security management. In practice, attackers often breach security protocols with specific incentives. For example, attackers manage to reap additional rewards by sabotaging computing tasks between two clouds. Unfortunately, most of the existing research works neglect this aspect when discussing the security of protocols. Furthermore, the construction of corrupting two parties is also missing in two-party computation. In this paper, we propose an incentive-driven attacking model where the attacker leverages corruption costs, benefits and possible consequences. We here formalize the utilities used for two-party protocols and the attacker(s), taking into account both corruption costs and attack benefits. Our proposed model can be considered as the extension of the seminal work presented by Groce and Katz (Annual international conference on the theory and applications of cryptographic techniques, Springer, Berlin, pp 81–98, 2012), while making significant contribution in addressing the corruption of two parties in two-party protocols. To the best of our knowledge, this is the first time to model the corruption of both parties in two-party protocols.


Publication metadata

Author(s): Wang Y, Metere R, Zhou H, Cui G, Li T

Publication type: Article

Publication status: Published

Journal: Soft Computing

Year: 2018

Volume: 22

Issue: 23

Pages: 7733-7740

Print publication date: 01/12/2018

Online publication date: 22/06/2018

Acceptance date: 02/04/2018

Date deposited: 03/07/2018

ISSN (print): 1432-7643

ISSN (electronic): 1433-7479

Publisher: Springer Verlag

URL: https://doi.org/10.1007/s00500-018-3342-3

DOI: 10.1007/s00500-018-3342-3


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Funding

Funder referenceFunder name
61771231
771066
61502218
ZR2017MF010
ZR2017MF062

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