scholarly journals SE-PSI: Fog/Cloud server-aided enhanced secure and effective private set intersection on scalable datasets with Bloom Filter

2021 ◽  
Vol 19 (2) ◽  
pp. 1861-1876
Author(s):  
Shuo Qiu ◽  
◽  
Zheng Zhang ◽  
Yanan Liu ◽  
Hao Yan ◽  
...  
Keyword(s):  
Big Data ◽  
Experimental Evaluation ◽  
High Efficiency ◽  
Bloom Filter ◽  
Medical System ◽  
Set Intersection ◽  
Cloud Server ◽  
Private Set Intersection ◽  
Enhance Efficiency ◽  
Application Requirements

<abstract><p>Private Set Intersection (PSI), which is a hot topic in recent years, has been extensively utilized in credit evaluation, medical system and so on. However, with the development of big data era, the existing traditional PSI cannot meet the application requirements in terms of performance and scalability. In this work, we proposed two secure and effective PSI (SE-PSI) protocols on scalable datasets by leveraging deterministic encryption and Bloom Filter. Specially, our first protocol focuses on high efficiency and is secure under a semi-honest server, while the second protocol achieves security on an economic-driven malicious server and hides the set/intersection size to the server. With experimental evaluation, our two protocols need only around 15 and 24 seconds respectively over one million-element datasets. Moreover, as a novelty, a <italic>multi-round</italic> mechanism is proposed for the two protocols to improve the efficiency. The implementation demonstrates that our <italic>two-round</italic> mechanism can enhance efficiency by almost twice than two basic protocols.</p></abstract>

scholarly journals Quantum private set intersection cardinality based on bloom filter

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bai Liu ◽  
Ou Ruan ◽  
Runhua Shi ◽  
Mingwu Zhang
Keyword(s):  
Privacy Protection ◽  
Data Privacy ◽  
Communication Complexity ◽  
Single Photon ◽  
Bloom Filter ◽  
Distributed Database ◽  
Single Photons ◽  
Practical Applications ◽  
Set Intersection ◽  
Private Set Intersection

AbstractPrivate Set Intersection Cardinality that enable Multi-party to privately compute the cardinality of the set intersection without disclosing their own information. It is equivalent to a secure, distributed database query and has many practical applications in privacy preserving and data sharing. In this paper, we propose a novel quantum private set intersection cardinality based on Bloom filter, which can resist the quantum attack. It is a completely novel constructive protocol for computing the intersection cardinality by using Bloom filter. The protocol uses single photons, so it only need to do some simple single-photon operations and tests. Thus it is more likely to realize through the present technologies. The validity of the protocol is verified by comparing with other protocols. The protocol implements privacy protection without increasing the computational complexity and communication complexity, which are independent with data scale. Therefore, the protocol has a good prospects in dealing with big data, privacy-protection and information-sharing, such as the patient contact for COVID-19.

scholarly journals Two-Party Privacy-Preserving Set Intersection with FHE

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1339
Author(s):  
Yunlu Cai ◽  
Chunming Tang ◽  
Qiuxia Xu
Keyword(s):  
Private Information ◽  
Homomorphic Encryption ◽  
Bloom Filter ◽  
Cloud Service ◽  
Fully Homomorphic Encryption ◽  
Cloud Service Provider ◽  
Set Size ◽  
Set Intersection ◽  
Learning With Errors ◽  
Private Set Intersection

A two-party private set intersection allows two parties, the client and the server, to compute an intersection over their private sets, without revealing any information beyond the intersecting elements. We present a novel private set intersection protocol based on Shuhong Gao’s fully homomorphic encryption scheme and prove the security of the protocol in the semi-honest model. We also present a variant of the protocol which is a completely novel construction for computing the intersection based on Bloom filter and fully homomorphic encryption, and the protocol’s complexity is independent of the set size of the client. The security of the protocols relies on the learning with errors and ring learning with error problems. Furthermore, in the cloud with malicious adversaries, the computation of the private set intersection can be outsourced to the cloud service provider without revealing any private information.

scholarly journals Efficient Implementation of Big Data Access Control Scheme with Privacy-Preserving Policy

2019 ◽  
Vol 8 (10) ◽  
pp. 3385-3395
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Access Control ◽  
Control Systems ◽  
Information Access ◽  
Bloom Filter ◽  
Data Access ◽  
Physical Control ◽  
Data Access Control ◽  
Cloud Server

In the time of big data, cloud computing, an immense measure of information can be created rapidly from different IT, non-IT related sources. Towards these big data, cloud computing, customary PC frameworks are not up to required skilled to store and process this information. Due to the adaptable and flexible figuring assets, distributed computing is a characteristic fit for putting away and preparing big data. With cloud computing, end-clients store their information into the cloud server and depend on the advanced cloud server to share their information to different clients. To share end-client's information to just approved clients, it is important to configuration access control systems as indicated by the prerequisites of end clients. When re-appropriating information into the cloud, end-clients free the physical control, virtual physical control of their information. In addition, cloud specialist co-ops are not completely trusted by end-clients, which make the entrance control additionally testing. on the off chance that the conventional access control systems (e.g., Access Control Lists) are connected, the cloud server turns into the judge to assess the entrance approach and settle on access choice. Subsequently, end-clients may stress that the cloud server may settle on wrong access choices purposefully or accidentally and uncover their information to some unapproved clients. To empower end-clients to control the entrance of their own information, a proficient and fine-grained huge information access control plot with protection saving strategy is proposed. In particular, the entire trait (as opposed to just its qualities) in the entrance strategies are scrambled. To help information decoding, encoding, a novel Attribute Bloom Filter is utilized [14][16] to assess whether a characteristic is in the entrance arrangement and find the accurate position in the entrance approach on the off chance that it is in the entrance strategy. Just the clients whose traits fulfill the entrance arrangement are qualified to unscramble the information.

Provably Secure Private Set Intersection With Constant Communication Complexity

2019 ◽  
Vol 9 (2) ◽  
pp. 39-64
Author(s):  
Sumit Kumar Debnath
Keyword(s):  
Communication Complexity ◽  
Bloom Filter ◽  
Security And Privacy ◽  
Data Sets ◽  
Indistinguishability Obfuscation ◽  
Security Parameter ◽  
Private Data ◽  
Set Intersection ◽  
Private Set Intersection ◽  
Probabilistic Data Structure

Electronic information is increasingly shared among unreliable entities. In this context, one interesting problem involves two parties that secretly want to determine an intersection of their respective private data sets while none of them wish to disclose the whole set to the other. One can adopt a Private Set Intersection (PSI) protocol to address this problem preserving the associated security and privacy issues. In this article, the authors present the first PSI protocol that incurs constant (p(k)) communication complexity with linear computation overhead and is fast even for the case of large input sets, where p(k) is a polynomial in security parameter k. Security of this scheme is proven in the standard model against semi-honest entities. The authors combine somewhere statistically binding (SSB) hash function with indistinguishability obfuscation (iO) and space-efficient probabilistic data structure Bloom filter to design the scheme.

scholarly journals Are you The One to Share? Secret Transfer with Access Structure

2017 ◽  
Vol 2017 (1) ◽  
pp. 149-169 ◽  
Author(s):  
Yongjun Zhao ◽  
Sherman S.M. Chow
Keyword(s):  
State Of The Art ◽  
Bloom Filter ◽  
Access Structure ◽  
Polynomial Evaluation ◽  
Threshold Policy ◽  
Oblivious Polynomial Evaluation ◽  
Set Intersection ◽  
Malicious Model ◽  
Private Set Intersection ◽  
The One

Abstract Sharing information to others is common nowadays, but the question is with whom to share. To address this problem, we propose the notion of secret transfer with access structure (STAS). STAS is a twoparty computation protocol that enables the server to transfer a secret to a client who satisfies the prescribed access structure. In this paper, we focus on threshold secret transfer (TST), which is STAS for threshold policy and can be made more expressive by using linear secret sharing. TST enables a number of applications including a simple construction of oblivious transfer (OT) with threshold access control, and (a variant of) threshold private set intersection (t-PSI), which are the first of their kinds in the literature to the best of our knowledge. The underlying primitive of STAS is a variant of OT, which we call OT for a sparse array. We provide two constructions which are inspired by state-of-the-art PSI techniques including oblivious polynomial evaluation (OPE) and garbled Bloom filter (GBF). The OPEbased construction is secure in the malicious model, while the GBF-based one is more efficient. We implemented the latter one and showed its performance in applications such as privacy-preserving matchmaking.

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