Mohammad Reza Zare Mirakabad, Aman Jantan, Stephane Bressan
언어
영어(ENG)
URL
https://www.earticle.net/Article/A103746
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
영어
Many efforts have been done in the field of privacy preservation to devise algorithms for data k-anonymization and l-diversification trying to protect privacy, by modification of data, for example. Fewer efforts have been made for devising techniques, tools and methodologies for investigation and evaluation of privacy risks. We are concerned about privacy diagnosis before starting protection. Actually we show privacy leakages threaten data publication. We introduce a Privacy Diagnosis Centre for this purpose. In this paper toward this diagnosis centre we focus on anonymity and, in particular, k-anonymity. Then we aim at k-anonymity diagnosis system. Such a system explores various questions about k-anonymity of data. “For which k is my data k-anonymous?”, “is my data sufficiently k-anonymous?”, “which subset and projection of data can be safely published to guarantee given k?”, “which information, if available from an outside source, threatens the k-anonymity of my data?” are examples of questions can be answered. We leverage two properties of k-anonymity that we express in the form of two lemmas. The first lemma is a monotonicity property that enables us to adapt the a-priori algorithm for k-anonymity. The second lemma, however, is a determinism property that enables us to devise an efficient algorithm for δ-suppression. We illustrate and empirically analyze the performance of the proposed algorithms.
목차
Abstract 1. Introduction 2. Literature review 3. Definitions of Important Terms 4. Framework of the Problem 4.1. What Questions Can be Asked? 4.2. Measuring k-anonymity given a quasi identifier S (Question 2) 4.3. Finding the largest quasi identifiers S that respect a given k-anonymity (Question 3) 4.4. Measuring k-anonymity of all combination of attributes 4.5. Measuring k-anonymity given a quasi identifier S and a maximum suppression threshold δ (Question 6) 5. Example 6. Case 7. Performance Evaluation 8. Conclusion and Future Works 9. References
저자
Mohammad Reza Zare Mirakabad [ Universiti Sains Malaysia ]
Aman Jantan [ Universiti Sains Malaysia ]
Stéphane Bressan [ National University of Singapore ]
보안공학연구지원센터(IJSIA) [Science & Engineering Research Support Center, Republic of Korea(IJSIA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Security and Its Applications
간기
격월간
pISSN
1738-9976
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Security and Its Applications Vol.3 No.1