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Betrayal, Distrust, and Rationality: Smart Counter-Collusion Contracts for Verifiable Cloud Computing

Lookup NU author(s): Dr Changyu Dong, Dr Yilei Wang, Amjad Aldweesh, Patrick Mccorry, Professor Aad van Moorsel

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by ACM, 2017.

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Abstract

Cloud computing has become an irreversible trend. Together comes the pressing need for verifiability, to assure the client the correctness of computation outsourced to the cloud. Existing verifiable computation techniques all have a high overhead, thus if being deployed in the clouds, would render cloud computing more expensive than the on-premises counterpart. To achieve verifiability at a reasonable cost, we leverage game theory and propose a smart contract based solution. In a nutshell, a client lets two clouds compute the same task, and uses smart contracts to stimulate tension, betrayal and distrust between the clouds, so that rational clouds will not collude and cheat. In the absence of collusion, verification of correctness can be done easily by crosschecking the results from the two clouds. We provide a formal analysis of the games induced by the contracts, and prove that the contracts will be effective under certain reasonable assumptions. By resorting to game theory and smart contracts, we are able to avoid heavy cryptographic protocols. The client only needs to pay two clouds to compute in the clear, and a small transaction fee to use the smart contracts. We also conducted a feasibility study that involves implementing the contracts in Solidity and running them on the official Ethereum network.


Publication metadata

Author(s): Dong C, Wang Y, Aldweesh A, McCorry P, van Moorsel A

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: CCS '17 Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

Year of Conference: 2017

Pages: 211-227

Online publication date: 03/11/2017

Acceptance date: 02/08/2017

Date deposited: 29/08/2017

Publisher: ACM

URL: https://doi.org/10.1145/3133956.3134032

DOI: 10.1145/3133956.3134032

Library holdings: Search Newcastle University Library for this item

ISBN: 9781450349468


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