Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity
Joint Authors
Tao, Xiaofeng
Khan, Razaullah
Anjum, Adeel
Sajjad, Haider
Malik, Saif ur Rehman
Khan, Abid
Amiri, Fatemeh
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-28
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Information Technology and Computer Science
Abstract EN
Privacy preserving data publishing (PPDP) refers to the releasing of anonymized data for the purpose of research and analysis.
A considerable amount of research work exists for the publication of data, having a single sensitive attribute.
The practical scenarios in PPDP with multiple sensitive attributes (MSAs) have not yet attracted much attention of researchers.
Although a recently proposed technique (p, k)-Angelization provided a novel solution, in this regard, where one-to-one correspondence between the buckets in the generalized table (GT) and the sensitive table (ST) has been used.
However, we have investigated a possibility of privacy leakage through MSA correlation among linkable sensitive buckets and named it as “fingerprint correlation fcorr attack.” Mitigating that in this paper, we propose an improved solution “c,k-anonymization” algorithm.
The proposed solution thwarts the fcorr attack using some privacy measures and improves the one-to-one correspondence to one-to-many correspondence between the buckets in GT and ST which further reduces the privacy risk with increased utility in GT.
We have formally modelled and analysed the attack and the proposed solution.
Experiments on the real-world datasets prove the outperformance of the proposed solution as compared to its counterpart.
American Psychological Association (APA)
Khan, Razaullah& Tao, Xiaofeng& Anjum, Adeel& Sajjad, Haider& Malik, Saif ur Rehman& Khan, Abid…[et al.]. 2020. Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1214530
Modern Language Association (MLA)
Khan, Razaullah…[et al.]. Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-18.
https://search.emarefa.net/detail/BIM-1214530
American Medical Association (AMA)
Khan, Razaullah& Tao, Xiaofeng& Anjum, Adeel& Sajjad, Haider& Malik, Saif ur Rehman& Khan, Abid…[et al.]. Privacy Preserving for Multiple Sensitive Attributes against Fingerprint Correlation Attack Satisfying c-Diversity. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1214530
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214530