Vulnerability- and Diversity-Aware Anonymization of PersonallyIdentifiable Information for Improving User Privacy and Utility ofPublishing Data

Collection with item attached
2017
Item details URL
http://open-repository.kisti.re.kr/cube/handle/open_repository/486951.do
DOI
10.3390/s17051059
Title
Vulnerability- and Diversity-Aware Anonymization of PersonallyIdentifiable Information for Improving User Privacy and Utility ofPublishing Data
Description
This work was supported by the Industrial Strategic TechnologyDevelopment Program (10047233, Development of Smart Home Web of ObjectArchitecture Technology) funded by the Ministry of Trade, Industry andEnergy (MOTIE, Korea).
abstract
Personally identifiable information (PII) affects individual privacy because PII combinations may yield unique identifications in published data. User PII such as age, race, gender, and zip code contain private information that may assist an adversary in determining the user to whom such information relates. Each item of user PII reveals identity differently, and some types of PII are highly identity vulnerable. More vulnerable types of PII enable unique identification more easily, and their presence in published data increases privacy risks. Existing privacy models treat all types of PII equally from an identity revelation point of view, and they mainly focus on hiding user PII in a crowd of other users. Ignoring the identity vulnerability of each type of PII during anonymization is not an effective method of protecting user privacy in a fine-grained manner. This paper proposes a new anonymization scheme that considers the identity vulnerability of PII to effectively protect user privacy. Data generalization is performed adaptively based on the identity vulnerability of PII as well as diversity to anonymize data. This adaptive generalization effectively enables anonymous data, which protects user identity and private information disclosures while maximizing the utility of data for performing analyses and building classification models. Additionally, the proposed scheme has low computational overheads. The simulation results show the effectiveness of the scheme and verify the aforementioned claims.
provenance
Made available in Cube on 2018-09-28T16:21:17Z (GMT). No. of bitstreams: 0
language
English
author
Majeed, Abdul
Ullah, Farman
Lee, Sungchang
accessioned
2018-09-28T16:21:17Z
available
2018-09-28T16:21:17Z
issued
2017
citation
SENSORS(17): 5
issn
1424-8220
uri
http://open-repository.kisti.re.kr/cube/handle/open_repository/486951.do
Funder
미래창조과학부
Funding Program
방송통신산업기술개발
Project ID
1711044559
Jurisdiction
Rep.of Korea
Project Name
Development of Smart Home Web of Objects Architecture
rights
openAccess
subject
personally identifiable information
identity vulnerability
diversity
adaptive generalization
privacy
utility
type
article


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