Practical Packing Method in Somewhat Homomorphic Encryption

Yasuda, Masaya; Shimoyama, Takeshi; Kogure, Jun; Yokoyama, Keitaro; Koshiba, Takeshi

doi:10.1007/978-3-642-54568-9_3

Cited by 32 publications

(28 citation statements)

References 18 publications

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“…For the proposed scheme, the value of the encrypted searchable index and the query is kept secret from Server 1. This is ensured by the strength of the Paillier cryp- 4 An example for group encryption tosystem. For Server 2, even though it knows the private key to the index and the query request, it could only obtain an intermediate result which will not indicate the original values of the index and the query request.…”

Section: Image Match With Secure Multi-party Computationmentioning

confidence: 99%

“…In order to further judge whether samples are similar, it requires data exchange with the user, which will increase the user's computational burden. In Yasuda's work [4], they developed a homomorphic encryption scheme for calculating Euclidean distance. Although the value of distance can be calculated, the comparison between two values, which is required in the process of image searching, is not implemented by their algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Privacy-Enhanced Similarity Search Scheme for Cloud Image Databases

Líu

Goto

2016

IEICE Trans. Inf. & Syst.

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SUMMARYThe privacy of users' data has become a big issue for cloud service. This research focuses on image cloud database and the function of similarity search. To enhance security for such database, we propose a framework of privacy-enhanced search scheme, while all the images in the database are encrypted, and similarity image search is still supported. key words: privacy-enhanced search, cloud service, content-based image retrieval (CBIR), homomorphic encryption, searchable encryption

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Section: Image Match With Secure Multi-party Computationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Privacy-Enhanced Similarity Search Scheme for Cloud Image Databases

Líu

Goto

2016

IEICE Trans. Inf. & Syst.

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“…As well as the secure inner product computation (6), linear combinations of two types of packed ciphertexts can give several meaningful computations such as (see also our related work [21]) http://www.pacific-mathforindustry.com/content/6/1/5…”

Section: Remark 2 (Privacy Enhance Technique)mentioning

confidence: 99%

Secret computation of purchase history data using somewhat homomorphic encryption

2014

Self Cite

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We consider secret computation of purchase history data among two companies of different type of business in order to identify purchase patterns without revealing customer information of each company. Among several privacy-preserving approaches, we focus on homomorphic encryption, which is public-key encryption supporting meaningful computations on encrypted data. In particular, we apply the somewhat homomorphic encryption scheme proposed by Brakerski and Vaikuntanathan (CRYPTO 2011), which can support a limited number of both additions and multiplications over polynomials. The main contribution is to introduce a practical packing method in the scheme to efficiently compute the set intersection of purchase history data over packed ciphertexts. Furthermore, we implemented the scheme for several parameters corresponding to various security levels, and demonstrate the efficiency of our packing method. We hope that this work would give the first practical usage of somewhat homomorphic encryption in marketing analysis.

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“…By mounting a variant of the hill climbing attack [5], performing multiple repeated attempts, each time carefully choosing v, the stored template b i can be retrieved. Such attacks against several protocols proposed in [6][7][8] are presented in [9][10][11]. Therefore, in similar applications it is important to verify the correctness of the outsourced computation, namely, the computation of XORing encrypted bitstrings.…”

Section: Introductionmentioning

confidence: 99%

“…There are also other protocols for privacy-preserving biometric authentication that are based on additive HE [14,20] such as [21] for face recognition and its subsequent improvement in [22], as well as the protocol in [23]. Yasuda et al proposed two biometric authentication protocols using somewhat HEs based on ideal lattices [6] and ring learning with errors [7], and the security of these protocols is scrutinised in [9,10]. In most of these schemes, biometric templates are extracted as bitstrings and the similarity of two biometric templates is measured by computing the Hamming distance between them.…”

Section: Introductionmentioning

confidence: 99%

Efficient Verifiable Computation of XOR for Biometric Authentication

Abidin

Aly

Rúa

et al. 2016

Cryptology and Network Security

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Abstract. This work addresses the security and privacy issues in remote biometric authentication by proposing an efficient mechanism to verify the correctness of the outsourced computation in such protocols. In particular, we propose an efficient verifiable computation of XORing encrypted messages using an XOR linear message authentication code (MAC) and we employ the proposed scheme to build a biometric authentication protocol. The proposed authentication protocol is both secure and privacy-preserving against malicious (as opposed to honestbut-curious) adversaries. Specifically, the use of the verifiable computation scheme together with an homomorphic encryption protects the privacy of biometric templates against malicious adversaries. Furthermore, in order to achieve unlinkability of authentication attempts, while keeping a low communication overhead, we show how to apply Oblivious RAM and biohashing to our protocol. We also provide a proof of security for the proposed solution. Our simulation results show that the proposed authentication protocol is efficient.

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Practical Packing Method in Somewhat Homomorphic Encryption

Cited by 32 publications

References 18 publications

Privacy-Enhanced Similarity Search Scheme for Cloud Image Databases

Privacy-Enhanced Similarity Search Scheme for Cloud Image Databases

Secret computation of purchase history data using somewhat homomorphic encryption

Efficient Verifiable Computation of XOR for Biometric Authentication

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