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

Authors: Tibor Jager (Ruhr-University Bochum), Andy Rupp (Karlsruhe Institute of Technology)

Volume: 2016
Issue: 3
Pages: 62–82

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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 noninteractive construction of a BBA system based on homomorphic commitments, digital signatures, and noninteractive 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.

Keywords: Loyalty systems, incentive collection, refund systems, participatory sensing, vehicle-to-grid, provable security.

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