Secure approximate pattern matching protocol via Boolean threshold private set intersection

Abstract

Approximate pattern matching (APM) measures whether the Hamming distance between two strings is less than a threshold value. APM has been widely utilized, such as gene matching and facial recognition.Yet, the genetic data are privacy-sensitive, resulting that the owners are unwilling to share the raw data. This inspires us to explore how to securely perform APM. After revisiting threshold private set intersection (TPSI), we first propose and formalize a functionality named Boolean threshold private set intersection (BTPSI). The new proposed BTPSI primitive returns a Boolean value (0 or 1) to the user, rather than the actual elements in TPSI. We then construct a secure protocol for the BTPSI functionality with semihonest security. Besides, we first combine oblivious transfer and BTPSI to achieve the efficient construction of secure approximate pattern matching (SAPM) protocol in a semihonest model. Furthermore, we implement our SAPM protocol to demonstrate its real practicality.The performance result shows that when the text length is 2 20 and the pattern length is 2 10 , the total runtime is less than 3 s.

A Novel Edge Cache-Based Private Set Intersection Protocol via Lightweight Oblivious PRF

“…without disc ing any more information. Note that we regard t as the set sizes for parties, n P as leader, and [ 1] i n P ∈ − as the client. The system model of the MPSI protocol is shown in Fig 3.…”

“…The PSI protocol guarantees that all parties can collaboratively calculate the intersection of the sets without disclosing anything beyond that intersection. PSI plays an important role in improving pattern matching [1], private contact discovery [2], advertisement conversion rate [3], and edge caching [4]. Edge caching is a key technology for communication networks.…”