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 Privacy Preserving Outsourced Calculations With Symmetric Fully Homomorphic Encryption

2019 ◽  
Vol 8 (10) ◽  
pp. 3012-3015
Keyword(s):  
Service Providers ◽  
Homomorphic Encryption ◽  
Cloud Service ◽  
New Paradigm ◽  
Fully Homomorphic Encryption ◽  
Privacy And Security ◽  
Cloud Service Provider ◽  
Privacy Concerns ◽  
Private Data ◽  
Cloud Storage Service

Cloud computing is a new paradigm which provides cloud storage service to manage, maintain and back up private data remotely. For privacy concerns the data is kept encrypted and made available to users on demand through cloud service provider over the internet. The legacy encryption techniques rely on sharing of keys, so service providers and end users of the cloud have exclusive rights on the data thus the secrecy may loss. Homomorphic Encryption is a significant encryption technique which allows users to perform limited arithmetic on the enciphered data without loss of privacy and security. This paper addresses a new simple and non-bootstrappable Fully Homomorphic Encryption Scheme based on matrices as symmetric keys with access control.

scholarly journals Achieving Lightweight Verifiable Privacy Preserving Search Over Encrypted Data

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Selasi Kwame Ocansey ◽  
Charles Fynn Oduro
Keyword(s):  
Service Provider ◽  
Homomorphic Encryption ◽  
Bloom Filter ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Data Sets ◽  
Cloud Service Provider ◽  
Encrypted Data ◽  
Security Proofs

When cloud clients outsource their database to the cloud, they entrust management operations to a cloud service provider who is expected to answer the client’s queries on the cloud where database is located. Efficient techniques can ensure critical requirements for outsourced data’s integrity and authenticity. A lightweight privacy preserving verifiable scheme for outsourcingdatabase securely is proposed, our scheme encrypts data before outsourcing and returned query results are verified with parameters of correctness and completeness. Our scheme is projected on lightweight homomorphic encryption technique and bloom filter which are efficiently authenticated to guarantee the outsourced database’s integrity, authenticity, and confidentiality. An ordering challenge technique is proposed for verifying top-k query results. We conclude by detailing our analysis of security proofs, privacy, verifiability and the performance efficiency of our scheme. Our proposed scheme’s proof and evaluation analysis show its security and efficiency for practical deployment. We also evaluate our scheme’s performances over two UCI data sets.

scholarly journals Multiparty Homomorphic Encryption from Ring-Learning-with-Errors

2021 ◽  
Vol 2021 (4) ◽  
pp. 291-311
Author(s):  
Christian Mouchet ◽  
Juan Troncoso-Pastoriza ◽  
Jean-Philippe Bossuat ◽  
Jean-Pierre Hubaux
Keyword(s):  
Private Information ◽  
Communication Complexity ◽  
Homomorphic Encryption ◽  
Secure Computation ◽  
Evaluation Procedure ◽  
Input Selection ◽  
Set Intersection ◽  
Broad Variety ◽  
Learning With Errors ◽  
Number Of Parties

Abstract We propose and evaluate a secure-multiparty-computation (MPC) solution in the semi-honest model with dishonest majority that is based on multiparty homomorphic encryption (MHE). To support our solution, we introduce a multiparty version of the Brakerski-Fan-Vercauteren homomorphic cryptosystem and implement it in an open-source library. MHE-based MPC solutions have several advantages: Their transcript is public, their o~ine phase is compact, and their circuit-evaluation procedure is noninteractive. By exploiting these properties, the communication complexity of MPC tasks is reduced from quadratic to linear in the number of parties, thus enabling secure computation among potentially thousands of parties and in a broad variety of computing paradigms, from the traditional peer-to-peer setting to cloud-outsourcing and smart-contract technologies. MHE-based approaches can also outperform the state-of-the-art solutions, even for a small number of parties. We demonstrate this for three circuits: private input selection with application to private-information retrieval, component-wise vector multiplication with application to private-set intersection, and Beaver multiplication triples generation. For the first circuit, privately selecting one input among eight thousand parties’ (of 32 KB each) requires only 1.31 MB of communication per party and completes in 61.7 seconds. For the second circuit with eight parties, our approach is 8.6 times faster and requires 39.3 times less communication than the current methods. For the third circuit and ten parties, our approach generates 20 times more triples per second while requiring 136 times less communication per-triple than an approach based on oblivious transfer. We implemented our scheme in the Lattigo library and open-sourced the code at github.com/ldsec/lattigo.

An Efficient Fully Homomorphic Encryption Scheme for Private Information Retrieval in the Cloud

2019 ◽  
Vol 34 (04) ◽  
pp. 2055008
Author(s):  
Xun Wang ◽  
Tao Luo ◽  
Jianfeng Li
Keyword(s):  
Information Retrieval ◽  
Theoretical Analysis ◽  
Private Information ◽  
Homomorphic Encryption ◽  
Private Information Retrieval ◽  
Encryption Scheme ◽  
Fully Homomorphic Encryption ◽  
Encrypted Data ◽  
Privacy Concerns ◽  
Simulation Results

Information retrieval in the cloud is common and convenient. Nevertheless, privacy concerns should not be ignored as the cloud is not fully trustable. Fully Homomorphic Encryption (FHE) allows arbitrary operations to be performed on encrypted data, where the decryption of the result of ciphertext operation equals that of the corresponding plaintext operation. Thus, FHE schemes can be utilized for private information retrieval (PIR) on encrypted data. In the FHE scheme proposed by Ducas and Micciancio (DM), only a single homomorphic NOT AND (NAND) operation is allowed between consecutive ciphertext refreshings. Aiming at this problem, an improved FHE scheme is proposed for efficient PIR where homomorphic additions and multiplications are based on linear operations on ciphertext vectors. Theoretical analysis shows that when compared with the DM scheme, the proposed scheme allows multiple homomorphic additions and a single homomorphic multiplication to be performed. The number of allowed homomorphic additions is determined by the ratio of the ciphertext modulus to the upper bound of initial ciphertext noise. Moreover, simulation results show that the proposed scheme is significantly faster than the DM scheme in the homomorphic evaluation for a series of algorithms.

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 VOTE: Verifiable Auditing for Outsourced Database with Token Enforced Cloud Storage

2019 ◽  
Vol 9 (2) ◽  
pp. 5156-5166
Keyword(s):  
Cloud Storage ◽  
Bloom Filter ◽  
Cloud Service ◽  
Communication Cost ◽  
Cloud Service Provider ◽  
Merkle Hash Tree ◽  
Database Administration ◽  
Outsourced Database ◽  
Counting Bloom Filter ◽  
Null Set

Database deploying is one of the remarkable utilities in cloud computing where the Information Proprietor (IP) assigns the database administration to the Cloud Service Provider (CSP) in order to lower the administration overhead and preservation expenditures of the database. Regardless of its overwhelming advantages, it experiences few security problems such as confidentiality of deployed database and auditability of search outcome. In recent past, survey has been carried out on the auditability of search outcome of deployed database that gives preciseness and intactness of search outcome. But in the prevailing schemes, since there is flow of data between IP and the clients repeatedly, huge communication cost is incurred at the Information Proprietor side. To address this challenge, we introduce Verifiable Auditing of Outsourced Database with Token Enforced Cloud Storage (VOTE) mechanism based on Merkle Hash Tree (MHT), Invertible Bloom Filter(IBF) and Counting Bloom Filter(CBF). The proposed scheme reduces the huge communication cost at the Information Proprietor side and achieves preciseness and intactness of the search outcome. Experimental analysis show that the proposed scheme has totally reduced the huge communication cost at the Information Proprietor side, and simultaneously achieves the preciseness and intactness of search outcome though the semi- trusted CSP deliberately sends a null set

scholarly journals Multi-Keyword Ranked Search in Cloud Storage using Homomorphic Indexing

2018 ◽  
Vol 7 (2.24) ◽  
pp. 243
Author(s):  
K Renugha ◽  
P Shanthi ◽  
A Umamakeswari
Keyword(s):  
Search Algorithm ◽  
Homomorphic Encryption ◽  
Cloud Service ◽  
Security And Privacy ◽  
Cloud Service Provider ◽  
Secure Information ◽  
Data Owner ◽  
Ranked Search ◽  
The Given ◽  
Is Outsourcing

In the cloud environment, the main issue is outsourcing of the information to the cloud service provider and outsider. Consider this, the cloud tenant store data in an encrypted form to achieve data security and privacy. The data owner needs the secure information sharing from the cloud and without leak of access pattern to the eavesdroppers. XOR homomorphic encryption searchable algorithm along with ranking is proposed to provide the security over the network. In addition our scheme provides secure Multi-keyword ranked search over encrypted data. Efficient ranked search algorithm returns the relevant document based on the results for the given multiple keywords. The experimental results prove that the system is efficient. 

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