Efficient Secure Multiparty Subset Computation

Joint Authors

Liu, Xin
Li, Shundong
Zhou, Sufang
Dou, Jiawei
Geng, Yaling

Source

Security and Communication Networks

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-08-28

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Information Technology and Computer Science

Abstract EN

Secure subset problem is important in secure multiparty computation, which is a vital field in cryptography.

Most of the existing protocols for this problem can only keep the elements of one set private, while leaking the elements of the other set.

In other words, they cannot solve the secure subset problem perfectly.

While a few studies have addressed actual secure subsets, these protocols were mainly based on the oblivious polynomial evaluations with inefficient computation.

In this study, we first design an efficient secure subset protocol for sets whose elements are drawn from a known set based on a new encoding method and homomorphic encryption scheme.

If the elements of the sets are taken from a large domain, the existing protocol is inefficient.

Using the Bloom filter and homomorphic encryption scheme, we further present an efficient protocol with linear computational complexity in the cardinality of the large set, and this is considered to be practical for inputs consisting of a large number of data.

However, the second protocol that we design may yield a false positive.

This probability can be rapidly decreased by reexecuting the protocol with different hash functions.

Furthermore, we present the experimental performance analyses of these protocols.

American Psychological Association (APA)

Zhou, Sufang& Li, Shundong& Dou, Jiawei& Geng, Yaling& Liu, Xin. 2017. Efficient Secure Multiparty Subset Computation. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1203233

Modern Language Association (MLA)

Zhou, Sufang…[et al.]. Efficient Secure Multiparty Subset Computation. Security and Communication Networks No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1203233

American Medical Association (AMA)

Zhou, Sufang& Li, Shundong& Dou, Jiawei& Geng, Yaling& Liu, Xin. Efficient Secure Multiparty Subset Computation. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1203233

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1203233