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Frontiers of Information Technology & Electronic Engineering

ISSN 2095-9184 (print), ISSN 2095-9230 (online)

Faster fog-aided private set intersection with integrity preserving

Abstract: Privat set intersection (PSI) allows two parties to compute the intersection of their private sets while revealing nothing except the intersection. With the development of fog computing, the need has arisen to delegate PSI on outsourced datasets to the fog. However, the existing PSI schemes are based on either fully homomorphic encryption (FHE) or pairing computation. To the best of our knowledge, FHE and pairing operations consume a huge amount of computational resource. It is therefore an untenable scenario for resource-limited clients to carry out these operations. Furthermore, these PSI schemes cannot be applied to fog computing due to some inherent problems such as unacceptable latency and lack of mobility support. To resolve this problem, we first propose a novel primitive called “faster fog-aided private set intersection with integrity preserving'', where the fog conducts delegated intersection operations over encrypted data without the decryption capacity. One of our technical highlights is to reduce the computation cost greatly by eliminating the FHE and pairing computation. Then we present a concrete construction and prove its security required under some cryptographic assumptions. Finally, we make a detailed theoretical analysis and simulation, and compare the results with those of the state-of-the-art schemes in two respects: communication overhead and computation overhead. The theoretical analysis and simulation show that our scheme is more efficient and practical.

Key words: Private set intersection, Fog computing, Verifiable, Data privacy

Chinese Summary  <20> 高效可验证的雾辅助私有集合交集计算

摘要:私有集合交集计算允许两方实体在不泄露除交集结果以外其他信息的前提下计算出两方实体的集合交集。随着雾计算的发展,将集合交集外包至雾的需求应运而生。然而,目前私有集合交集计算都是基于全同态加密和配对操作,所需代价较高且不支持移动,难以在雾计算中应用。提出一种高效可验证的雾辅助私有集合交集计算方案。在该方案中,实体将私有集合交集计算外包至雾,雾在没有解密能力的前提下计算集合交集。该方案不依赖全同态加密和配对操作,极大提高了计算效率。此外,构建并证明了该方案的安全性。最后,对比分析本方案与其他方案的通信复杂度和计算复杂度。分析结果表明,该方案更高效,更具现实意义。

关键词组:私有集合交集计算;雾计算;可验证;数据隐私


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DOI:

10.1631/FITEE.1800518

CLC number:

TP309

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On-line Access:

2019-01-07

Received:

2018-08-30

Revision Accepted:

2018-11-11

Crosschecked:

2018-12-17

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