The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
안전한 쌍방 비교는 개인 정보 보호 데이터 마이닝 및 기계 학습과 같은 많은 개인 정보 보호 애플리케이션에서 중요한 역할을 합니다. 특히, 적절한 입력/출력 구성을 갖춘 사용 가능한 비교 프로토콜은 이러한 애플리케이션의 성능에 상당한 영향을 미칩니다. 본 문서에서는 먼저 이러한 프로토콜에 사용되는 다양한 구성을 체계적인 방식으로 설명할 수 있는 안전한 두 당사자 비교 프로토콜의 분류 체계를 설명합니다. 이 분류법을 통해 총 216가지 유형의 비교 프로토콜이 생성됩니다. 그런 다음 이러한 유형 간의 변환을 설명합니다. 이러한 변환은 알려진 기술을 기반으로 하며 이전에 명시적으로 또는 암시적으로 고려되었지만 Nergiz et al은 이러한 변환 기술의 조합을 사용하여 덜 알려진 두 당사자 비교 프로토콜을 변환할 수 있음을 보여줍니다. (IEEE SocialCom 2010)은 두 당사자가 비교되는 값의 공유를 보유하고 비교 결과의 공유를 얻는 구성에서 매우 효율적인 프로토콜로 변환되었습니다. 이 설정은 다자간 계산 프로토콜에서 자주 사용되므로 많은 개인 정보 보호 애플리케이션에서도 사용됩니다. 우리는 또한 프로토콜을 구현하고 성능을 측정합니다. 우리의 측정에 따르면 오프라인 사전 계산이 허용되지 않는 경우 이 프로토콜은 이 입력/출력 구성에 대해 이전에 제안된 프로토콜보다 성능이 뛰어납니다.
Nuttapong ATTRAPADUNG
National Institute of Advanced Industrial Science and Technology (AIST)
Goichiro HANAOKA
National Institute of Advanced Industrial Science and Technology (AIST)
Shinsaku KIYOMOTO
KDDI Research, Inc
Tomoaki MIMOTO
KDDI Research, Inc
Jacob C. N. SCHULDT
National Institute of Advanced Industrial Science and Technology (AIST)
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Nuttapong ATTRAPADUNG, Goichiro HANAOKA, Shinsaku KIYOMOTO, Tomoaki MIMOTO, Jacob C. N. SCHULDT, "A Taxonomy of Secure Two-Party Comparison Protocols and Efficient Constructions" in IEICE TRANSACTIONS on Fundamentals,
vol. E102-A, no. 9, pp. 1048-1060, September 2019, doi: 10.1587/transfun.E102.A.1048.
Abstract: Secure two-party comparison plays a crucial role in many privacy-preserving applications, such as privacy-preserving data mining and machine learning. In particular, the available comparison protocols with the appropriate input/output configuration have a significant impact on the performance of these applications. In this paper, we firstly describe a taxonomy of secure two-party comparison protocols which allows us to describe the different configurations used for these protocols in a systematic manner. This taxonomy leads to a total of 216 types of comparison protocols. We then describe conversions among these types. While these conversions are based on known techniques and have explicitly or implicitly been considered previously, we show that a combination of these conversion techniques can be used to convert a perhaps less-known two-party comparison protocol by Nergiz et al. (IEEE SocialCom 2010) into a very efficient protocol in a configuration where the two parties hold shares of the values being compared, and obtain a share of the comparison result. This setting is often used in multi-party computation protocols, and hence in many privacy-preserving applications as well. We furthermore implement the protocol and measure its performance. Our measurement suggests that the protocol outperforms the previously proposed protocols for this input/output configuration, when off-line pre-computation is not permitted.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E102.A.1048/_p
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@ARTICLE{e102-a_9_1048,
author={Nuttapong ATTRAPADUNG, Goichiro HANAOKA, Shinsaku KIYOMOTO, Tomoaki MIMOTO, Jacob C. N. SCHULDT, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Taxonomy of Secure Two-Party Comparison Protocols and Efficient Constructions},
year={2019},
volume={E102-A},
number={9},
pages={1048-1060},
abstract={Secure two-party comparison plays a crucial role in many privacy-preserving applications, such as privacy-preserving data mining and machine learning. In particular, the available comparison protocols with the appropriate input/output configuration have a significant impact on the performance of these applications. In this paper, we firstly describe a taxonomy of secure two-party comparison protocols which allows us to describe the different configurations used for these protocols in a systematic manner. This taxonomy leads to a total of 216 types of comparison protocols. We then describe conversions among these types. While these conversions are based on known techniques and have explicitly or implicitly been considered previously, we show that a combination of these conversion techniques can be used to convert a perhaps less-known two-party comparison protocol by Nergiz et al. (IEEE SocialCom 2010) into a very efficient protocol in a configuration where the two parties hold shares of the values being compared, and obtain a share of the comparison result. This setting is often used in multi-party computation protocols, and hence in many privacy-preserving applications as well. We furthermore implement the protocol and measure its performance. Our measurement suggests that the protocol outperforms the previously proposed protocols for this input/output configuration, when off-line pre-computation is not permitted.},
keywords={},
doi={10.1587/transfun.E102.A.1048},
ISSN={1745-1337},
month={September},}
부
TY - JOUR
TI - A Taxonomy of Secure Two-Party Comparison Protocols and Efficient Constructions
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1048
EP - 1060
AU - Nuttapong ATTRAPADUNG
AU - Goichiro HANAOKA
AU - Shinsaku KIYOMOTO
AU - Tomoaki MIMOTO
AU - Jacob C. N. SCHULDT
PY - 2019
DO - 10.1587/transfun.E102.A.1048
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E102-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2019
AB - Secure two-party comparison plays a crucial role in many privacy-preserving applications, such as privacy-preserving data mining and machine learning. In particular, the available comparison protocols with the appropriate input/output configuration have a significant impact on the performance of these applications. In this paper, we firstly describe a taxonomy of secure two-party comparison protocols which allows us to describe the different configurations used for these protocols in a systematic manner. This taxonomy leads to a total of 216 types of comparison protocols. We then describe conversions among these types. While these conversions are based on known techniques and have explicitly or implicitly been considered previously, we show that a combination of these conversion techniques can be used to convert a perhaps less-known two-party comparison protocol by Nergiz et al. (IEEE SocialCom 2010) into a very efficient protocol in a configuration where the two parties hold shares of the values being compared, and obtain a share of the comparison result. This setting is often used in multi-party computation protocols, and hence in many privacy-preserving applications as well. We furthermore implement the protocol and measure its performance. Our measurement suggests that the protocol outperforms the previously proposed protocols for this input/output configuration, when off-line pre-computation is not permitted.
ER -