Scalable Privacy-Preserving <I>t</I>-Repetition Protocol with Distributed Medical Data

Ji Young CHUN; Dowon HONG; Dong Hoon LEE; Ik Rae JEONG

doi:10.1587/transfun.E95.A.2451

Scalable Privacy-Preserving t-Repetition Protocol with Distributed Medical Data

Ji Young CHUN, Dowon HONG, Dong Hoon LEE, Ik Rae JEONG

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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.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E95-A No.12 pp.2451-2460

Publication Date: 2012/12/01

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Online ISSN: 1745-1337

DOI: 10.1587/transfun.E95.A.2451

Type of Manuscript: PAPER

Category: Cryptography and Information Security

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Ji Young CHUN, Dowon HONG, Dong Hoon LEE, Ik Rae JEONG, "Scalable Privacy-Preserving t-Repetition Protocol with Distributed Medical Data" in IEICE TRANSACTIONS on Fundamentals, vol. E95-A, no. 12, pp. 2451-2460, December 2012, doi: 10.1587/transfun.E95.A.2451.
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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E95.A.2451/_p

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@ARTICLE{e95-a_12_2451,
author={Ji Young CHUN, Dowon HONG, Dong Hoon LEE, Ik Rae JEONG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Scalable Privacy-Preserving t-Repetition Protocol with Distributed Medical Data},
year={2012},
volume={E95-A},
number={12},
pages={2451-2460},
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.},
keywords={},
doi={10.1587/transfun.E95.A.2451},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - Scalable Privacy-Preserving t-Repetition Protocol with Distributed Medical Data
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2451
EP - 2460
AU - Ji Young CHUN
AU - Dowon HONG
AU - Dong Hoon LEE
AU - Ik Rae JEONG
PY - 2012
DO - 10.1587/transfun.E95.A.2451
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E95-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2012
AB - 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.
ER -