A two-party privacy preserving set intersection protocol against malicious users in cloud computing

Cao, Xiaofeng; Li, Hui; Dang, Lanjun; Lin, Yin

doi:10.1016/j.csi.2016.08.004

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…Compared with the classical related protocols, our solution has the advantage of higher security and lower communication complexity. In addition, our proposed protocol can also be extended to some other complicated privacy-preserving computation problems, such as privacy-preserving database queries over cloud data [Cao, Wang, Li et al (2014); Shen, Li, Li et al (2017)], privacy-preserving set operations in cloud computing [Cao, Li, Dang et al (2017); Zhuo, Jia, Guo et al 2017], and privacy-preserving reversible data hiding over encrypted image [Cao, Du, Wei et al (2016)]. Furthermore, the method of the oracle operation applied in the presented protocols is general and can be employed to solve other similar privacy-preserving computation geometry problems, such as convex hull, polygon inclusion, etc.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Privacy-Preserving Quantum Two-Party Geometric Intersection

Liu¹,

Xu²,

Yang³

et al. 2019

Computers, Materials &Amp; Continua

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www.techscience.com/cmc) into the quantum states, and then the oracle operation f O is applied to obtain a new quantum state which includes the XOR results between each element of A S and B S. Finally, the quantum counting is introduced to get the amount (t) of the states i j a b ⊕ equaling to 0 , and the intersection result can be obtained by judging 0 t > or not. Compared with classical PGI protocols, our proposed protocol not only has higher security, but also holds lower communication complexity.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Privacy-Preserving Quantum Two-Party Geometric Intersection

Liu¹,

Xu²,

Yang³

et al. 2019

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Of course, these methods reach much further than only these examples: MPSI protocols can be used among several commercial companies to find the intersection of customer lists where each list, except the intersection, is protected. The list of common customers can be used to plan promotions for such customers [14]; MPSI can be used among the community of medical professionals to find out the patients of a hospital who has participated in the medical tests of different research labs [15]; MPSI can also be used in multi-party access control, where several coowners of a common content each specify a set of users who are permitted to access data. The ones in the intersection are allowed to access the content [16]; MPSI can be employed among several enterprises which have private audit logs of connections to their corporate networks and are interested in identifying similar activities in all networks [17].…”

Section: Introductionmentioning

confidence: 99%

Practical Multi-Party Private Set Intersection Protocols

Bay

Erkin

Hoepman

et al. 2022

IEEE Trans.Inform.Forensic Secur.

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Privacy-preserving techniques for processing sets of information have attracted the research community's attention in recent years due to society's increasing dependency on the availability of data at any time. One of the fundamental problems in set operations is known as Private Set Intersection (PSI). The problem requires two parties to compute the intersection between their sets while preserving correctness and privacy. Although several efficient two-party PSI protocols already exist, protocols for PSI in the multi-party setting (MPSI) currently scale poorly with a growing number of parties, even though this applies to many real-life scenarios. This paper fills this gap by proposing two multi-party protocols based on Bloom filters and threshold homomorphic PKEs, which are secure in the semi-honest model. The first protocol is a multi-party PSI, whereas the second provides a more subtle functionalitythreshold multi-party PSI (T-MPSI) -which outputs items of the server that appear in at least some number of other private sets. The protocols are inspired by the Davidson-Cid protocol based on Bloom filters. We compare our MPSI protocol against Kolesnikov et al., which is among the fastest known MPSI protocols. Our MPSI protocol performs better than Kolesnikov et al. in terms of run time, given that the sets are small and there is a large number of parties. Our T-MPSI protocol performs better than other existing works: the computational and communication complexities are linear in the number of elements in the largest set given a fixed number of colluding parties. We conclude that our MPSI and T-MPSI protocols are practical solutions suitable for emerging use-case scenarios with many parties, where previous solutions did not scale well.

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“…Researchers have given multiple approaches to address this issue. Some privacy-preserving protocols [39], [40] are proposed based on aggregate signature [14] or hash-based commitment [15] but auditing is not mentioned in these schemes. Huang et al [18] proposed privacy-preserving scheme using group signature and blockchain.…”

Section: Introductionmentioning

confidence: 99%

Privacy Preserving Dynamic Provable Data Possession with Batch Update for Secure Cloud Storage

Chaudhari¹,

Swain²

2021

IJACSA

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Cloud Server (CS) is an untrusted entity in cloud paradigm that may hide accidental data loss to maintain its reputation. Provable Data Possession (PDP) is a model that allows Third Party Auditor (TPA) to verify the integrity of outsourced data on behalf of cloud user without downloading the data files. But this public auditing model faces many security and performance issues such as: unnecessary computational burden on user as well as on TPA, to preserve identities of users from TPA during auditing, support for dynamic updates etc. Many PDP schemes creates computational burden either on TPA or Cloud User. To balance this overhead between TPA and User, this paper proposes Privacy-Preserving Dynamic Provable Data Possession (P 2 DPDP) scheme, which is based on ODPDP scheme. In ODPDP scheme, user relieves the burden by signing a contract with TPA regarding verification of his outsourced data. But this scheme generates computation overhead on TPA. To reduce this computation overhead of TPA, our P 2 DPDP scheme uses Indistinguishability Obfuscation (IO) with one-way function such as message authentication code to make a lightweight auditing process. P 2 DPDP scheme uses Rank-based Merkle Tree (RBMT) to support dynamic updates in batch mode which greatly reduces computation overhead of TPA. ODPDP lacks privacy which is maintained in P 2 DPDP using ring signature technique. Our experimental results demonstrate the reduced verification time and computation cost compared to existing schemes.

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A two-party privacy preserving set intersection protocol against malicious users in cloud computing

Cited by 10 publications

References 20 publications

Privacy-Preserving Quantum Two-Party Geometric Intersection

Privacy-Preserving Quantum Two-Party Geometric Intersection

Practical Multi-Party Private Set Intersection Protocols

Privacy Preserving Dynamic Provable Data Possession with Batch Update for Secure Cloud Storage

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