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Black-Box Accumulation: Collecting Incentives in a Privacy-Preserving Way

Black-Box Accumulation: Collecting Incentives in a Privacy-Preserving Way Abstract We formalize and construct black-box accumulation (BBA), a useful building block for numerous important user-centric protocols including loyalty systems, refund systems, and incentive systems (as, e.g., employed in participatory sensing and vehicle-to-grid scenarios). A core requirement all these systems share is a mechanism to let users collect and sum up values (call it incentives, bonus points, reputation points, etc.) issued by some other parties in a privacy-preserving way such that curious operators may not be able to link the different transactions of a user. At the same time, a group of malicious users may not be able to cheat the system by pretending to have collected a higher amount than what was actually issued to them. As a first contribution, we fully formalize the core functionality and properties of this important building block. Furthermore, we present a generic and non-interactive construction of a BBA system based on homomorphic commitments, digital signatures, and non-interactive zero-knowledge proofs of knowledge. For our construction, we formally prove security and privacy properties. Finally, we propose a concrete instantiation of our construction using Groth-Sahai commitments and proofs as well as the optimal structure-preserving signature scheme of Abe et al. and analyze its efficiency. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings on Privacy Enhancing Technologies de Gruyter

Black-Box Accumulation: Collecting Incentives in a Privacy-Preserving Way

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Publisher
de Gruyter
Copyright
Copyright © 2016 by the
ISSN
2299-0984
eISSN
2299-0984
DOI
10.1515/popets-2016-0016
Publisher site
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Abstract

Abstract We formalize and construct black-box accumulation (BBA), a useful building block for numerous important user-centric protocols including loyalty systems, refund systems, and incentive systems (as, e.g., employed in participatory sensing and vehicle-to-grid scenarios). A core requirement all these systems share is a mechanism to let users collect and sum up values (call it incentives, bonus points, reputation points, etc.) issued by some other parties in a privacy-preserving way such that curious operators may not be able to link the different transactions of a user. At the same time, a group of malicious users may not be able to cheat the system by pretending to have collected a higher amount than what was actually issued to them. As a first contribution, we fully formalize the core functionality and properties of this important building block. Furthermore, we present a generic and non-interactive construction of a BBA system based on homomorphic commitments, digital signatures, and non-interactive zero-knowledge proofs of knowledge. For our construction, we formally prove security and privacy properties. Finally, we propose a concrete instantiation of our construction using Groth-Sahai commitments and proofs as well as the optimal structure-preserving signature scheme of Abe et al. and analyze its efficiency.

Journal

Proceedings on Privacy Enhancing Technologies – de Gruyter

Published: Jul 1, 2016

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