kbe-Anonymity: Test Data Anonymization for Evolving Programs

High-quality test data that is useful for effective testing is often available on users’ site. However, sharing data owned by users with software vendors may raise privacy concerns. Techniques are needed to enable data sharing among data owners and the vendors without leaking data privacy. Evolving...

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Main Authors: Lucia, -, LO, David, JIANG, Lingxiao, Budi, Aditya
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2012
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Online Access:https://ink.library.smu.edu.sg/sis_research/1572
http://dl.acm.org/citation.cfm?id=2351718
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-25712012-09-24T03:48:42Z kbe-Anonymity: Test Data Anonymization for Evolving Programs Lucia, - LO, David JIANG, Lingxiao Budi, Aditya High-quality test data that is useful for effective testing is often available on users’ site. However, sharing data owned by users with software vendors may raise privacy concerns. Techniques are needed to enable data sharing among data owners and the vendors without leaking data privacy. Evolving programs bring additional challenges because data may be shared multiple times for every version of a program. When multiple versions of the data are cross-referenced, private information could be inferred. Although there are studies addressing the privacy issue of data sharing for testing and debugging, little work has explicitly addressed the challenges when programs evolve. In this paper, we examine kb-anonymity that is recently proposed for anonymizing data for a single version of a program, and identify a potential privacy risk if it is repeatedly applied for evolving programs. We propose kbe-anonymity to address the insufficiencies of kb-anonymity and evaluate our model on three Java programs. We demonstrate that kbe -anonymity can successfully address the potential risk of kb-anonymity, maintain sufficient path coverage for testing, and be as efficient as kb-anonymity. 2012-09-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/1572 info:doi/10.1145/2351676.2351718 http://dl.acm.org/citation.cfm?id=2351718 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University k-anonymity behavior preservation privacy preservation testing and debugging Computer Sciences Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic k-anonymity
behavior preservation
privacy preservation
testing and debugging
Computer Sciences
Software Engineering
spellingShingle k-anonymity
behavior preservation
privacy preservation
testing and debugging
Computer Sciences
Software Engineering
Lucia, -
LO, David
JIANG, Lingxiao
Budi, Aditya
kbe-Anonymity: Test Data Anonymization for Evolving Programs
description High-quality test data that is useful for effective testing is often available on users’ site. However, sharing data owned by users with software vendors may raise privacy concerns. Techniques are needed to enable data sharing among data owners and the vendors without leaking data privacy. Evolving programs bring additional challenges because data may be shared multiple times for every version of a program. When multiple versions of the data are cross-referenced, private information could be inferred. Although there are studies addressing the privacy issue of data sharing for testing and debugging, little work has explicitly addressed the challenges when programs evolve. In this paper, we examine kb-anonymity that is recently proposed for anonymizing data for a single version of a program, and identify a potential privacy risk if it is repeatedly applied for evolving programs. We propose kbe-anonymity to address the insufficiencies of kb-anonymity and evaluate our model on three Java programs. We demonstrate that kbe -anonymity can successfully address the potential risk of kb-anonymity, maintain sufficient path coverage for testing, and be as efficient as kb-anonymity.
format text
author Lucia, -
LO, David
JIANG, Lingxiao
Budi, Aditya
author_facet Lucia, -
LO, David
JIANG, Lingxiao
Budi, Aditya
author_sort Lucia, -
title kbe-Anonymity: Test Data Anonymization for Evolving Programs
title_short kbe-Anonymity: Test Data Anonymization for Evolving Programs
title_full kbe-Anonymity: Test Data Anonymization for Evolving Programs
title_fullStr kbe-Anonymity: Test Data Anonymization for Evolving Programs
title_full_unstemmed kbe-Anonymity: Test Data Anonymization for Evolving Programs
title_sort kbe-anonymity: test data anonymization for evolving programs
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/sis_research/1572
http://dl.acm.org/citation.cfm?id=2351718
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