arrow
Return

Efficient Secure Pattern Matching With Malicious Adversaries

delete2020-01-01
delete2
PRE
AI
M
Maryam Zarezadeh
H
Hamid Mala *
B
Behrouz Tork Ladani
DOI:10.1109/TDSC.2020.3009595delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
In a secure pattern matching scheme, a client learns only the locations where his private pattern matches a server's private text, while server learns nothing. In this article, we propose a secure pattern matching protocol for the semi-honest setting which is then enhanced to guarantee full simulation-based security in the presence of malicious parties. The proposed protocol supports exact pattern matching, approximate pattern matching and pattern matching with wildcards. It is analytically shown that the proposed protocol is considerably more efficient in the approximate matching with at most k permitted mismatches while it has the same speed in the exact matching case comparing with the recent work in the literature. The achievements are also experimentally evaluated on a case of secure Desoxyribo-Nucleic Acid (DNA) search over the NCBI dataset of the United States national library of medicine. The results show efficiency of the proposed protocol and particularly confirm low computation overhead for the client.
Keywords:
Pattern matching
malicious adversary
secure multiparty computation
full simulation
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Dependable and Secure Computing cover
IEEE Transactions on Dependable and Secure Computing
IF:
7.5
Papers:
2.4K
Citations:
9.6K

Organization

U
University of Isfahan
Scholars:
4.5K
Papers: 4.1K
Citations: 5