Scalable Privacy-Preserving t-Repetition Protocol with Distributed Medical Data
- Authors
- Chun, Ji Young; Hong, Dowon; Lee, Dong Hoon; Jeong, Ik Rae
- Issue Date
- 12월-2012
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- t-repetition; rare cases; set operation; data mining; privacy
- Citation
- IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, v.E95A, no.12, pp.2451 - 2460
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
- Volume
- E95A
- Number
- 12
- Start Page
- 2451
- End Page
- 2460
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/106813
- DOI
- 10.1587/transfun.E95.A.2451
- ISSN
- 0916-8508
- Abstract
- Finding rare cases with medical data is important when hospitals or research institutes want to identify rare diseases. To extract meaningful information from a large amount of sensitive medical data, privacy-preserving data mining techniques can be used. A privacy-preserving t-repetition protocol can be used to find rare cases with distributed medical data. A privacy-preserving t-repetition protocol is to find elements which exactly t parties out of n parties have in common in their datasets without revealing their private datasets. A privacy-preserving t-repetition protocol can be used to find not only common cases with a high t but also rare cases with a low t. In 2011, Chun et al. suggested the generic set operation protocol which can be used to find t-repeated elements. In the paper, we first show that the Chun et al's protocol becomes infeasible for calculating t-repeated elements if the number of users is getting bigger. That is, the computational and communicational complexities of the Chun et al.'s protocol in calculating t-repeated elements grow exponentially as the number of users grows. Then, we suggest a polynomial-time protocol with respect to the number of users, which calculates t-repeated elements between users.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - School of Cyber Security > Department of Information Security > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.