NDLI: K-anonymity on sensitive transaction items

Content Provider	IEEE Xplore Digital Library
Author	Shyue-Liang Wang Yu-Chuan Tsai Hung-Yu Kao Tzung-Pei Hong
Copyright Year	2011
Description	Author affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan 70101 (Yu-Chuan Tsai; Hung-Yu Kao) \|\| Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan 81148 (Tzung-Pei Hong) \|\| Department of Information Management Engineering, National University of Kaohsiung, Kaohsiung, Taiwan 81148 (Shyue-Liang Wang)
Abstract	K-anonymity-based techniques [9], [11], [15]–[17] have been the main anonymization techniques on relational data ad transactional data to protect privacy against re-identification attacks. Assuming the existence of both sensitive attributes and quasi-identifier (QI) attributes, a relational dataset D is k-anonymous if every record in D has at least k-1 other records with identical quasi-identifier attribute values, but with different sensitive attribute values. However, existing k-anonymity on transactional data treats all items as quasi-identifiers. The anonymized data set has k identical transactions in groups and suffered from lower data utility [6]–[7][10][18]–[19]. In this work, we propose a new anonymity concept on transactional data with quasi-identifier items and sensitive items (SI). For a transaction that contains sensitive items, there must exist at least k-1 other identical transactions [5][20]. For a transaction that does not contain sensitive item, no anonymization is required. A transactional data set satisfying this property is called sensitive k-anonymous. We proposed two algorithms, Sensitive Transaction Neighbors (STN) and Gray Sort Clustering (GSC), by adding/deleting QI items and adding SI items to achieve sensitive k-anonymity on transactional data. Extensive numerical experiments were given to demonstrate the characteristics of the proposed concept and approaches.
Starting Page	723
Ending Page	727
File Size	318052
Page Count	5
File Format	PDF
ISBN	9781457703720
e-ISBN	9781457703713
DOI	10.1109/GRC.2011.6122687
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-08
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data privacy Privacy anonymization Itemsets Publishing transaction data sensitive k-anonymity privacy preservation Clustering algorithms Silicon Reflective binary codes
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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