Privacy-preserving data mashup

Mohammed, Noman; Fung, Benjamin C. M.; Ke, Wang; Hung, Patrick C. K.

doi:10.1145/1516360.1516388

Cited by 41 publications

(25 citation statements)

References 45 publications

(71 reference statements)

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“…There are some distributed anonymization methods in vertically partitioned data [10,14,6]. Mohammed et al [10,14] used the top-down approach and some secure computation protocols [9,15] in order to join the tables in multiple providers.…”

Section: Related Workmentioning

confidence: 99%

“…Mohammed et al [10,14] used the top-down approach and some secure computation protocols [9,15] in order to join the tables in multiple providers. The top-down approach is an algorithm to specialize a value qid of a quasiidentifier in the tables step by step.…”

Section: Related Workmentioning

confidence: 99%

“…Existing distributed anonymization protocols assume that the sets of the users in Providers A and B are the same [4,10,7,6]. In other words, each user who exists in Provider A also exists in Provider B.…”

Section: Problem Of Revealing the Existence Of A Usermentioning

confidence: 99%

“…We use an "Adult" data set in UCI Repository [2]. Furthermore, we divide the "Adult" data set the same way as Mohammed et al [10].…”

Section: Experimental Evaluationmentioning

confidence: 99%

See 3 more Smart Citations

Distributed Data Federation without Disclosure of User Existence

Takenouchi

Kawamura

Ohsuga

2012

Data and Applications Security and Privacy XXVI

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Abstract. Service providers collect user's personal information relevant to their businesses. Personal information stored by different service providers is expected to be combined to make new services. However, specific user records risk being identified from the combined personal information, and the user's sensitive information may be revealed. Also, personal information collected by a service provider must not be disclosed to other service providers because of security issues. Thus, several researchers have been investigating distributed anonymization protocols, which combine the personal information stored by the providers and sanitize it to ensure an anonymity policy with minimum disclosure. However, when providers have different sets of the users, there is a problem that the existence of users in either service provider may be revealed. This paper introduces a new notion, δ-max-site-presence, which indicates the probability of the existence of users being revealed in a distributed environment and a new distributed anonymization protocol for hiding the existence of users. Our evaluation results show that the proposed protocol can anonymize users in accordance with the policy of hiding their existence and user anonymity without too much information loss.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Problem Of Revealing the Existence Of A Usermentioning

confidence: 99%

“…We use an "Adult" data set in UCI Repository [2]. Furthermore, we divide the "Adult" data set the same way as Mohammed et al [10].…”

Section: Experimental Evaluationmentioning

confidence: 99%

See 2 more Smart Citations

Distributed Data Federation without Disclosure of User Existence

Takenouchi

Kawamura

Ohsuga

2012

Data and Applications Security and Privacy XXVI

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“…[5], [6], [23] studied distributed anonymization for vertically partitioned data using k-anonymity. Zhong et al [24] studied classification on data collected from individual data owners (each record is contributed by one data owner) while maintaining k-anonymity.…”

Section: Anonymization For M-privacymentioning

confidence: 99%

m-Privacy for Collaborative Data Publishing

Goryczka

Xiong

Fung³

2011

Proceedings of the 7th International Conference on Collaborative Computing: Networking, Applications and Worksharing

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Abstract-In this paper, we consider the collaborative data publishing problem for anonymizing horizontally partitioned data at multiple data providers. We consider a new type of "insider attack" by colluding data providers who may use their own data records (a subset of the overall data) in addition to the external background knowledge to infer the data records contributed by other data providers. The paper addresses this new threat and makes several contributions. First, we introduce the notion of m-privacy, which guarantees that the anonymized data satisfies a given privacy constraint against any group of up to m colluding data providers. Second, we present heuristic algorithms exploiting the equivalence group monotonicity of privacy constraints and adaptive ordering techniques for efficiently checking m-privacy given a set of records. Finally, we present a data provider-aware anonymization algorithm with adaptive mprivacy checking strategies to ensure high utility and m-privacy of anonymized data with efficiency. Experiments on real-life datasets suggest that our approach achieves better or comparable utility and efficiency than existing and baseline algorithms while providing m-privacy guarantee.

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Methods to Mitigate Risk of Composition Attack in Independent Data Publications

Sattar

Baig

et al. 2015

Medical Data Privacy Handbook

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Privacy-preserving data mashup

Cited by 41 publications

References 45 publications

Distributed Data Federation without Disclosure of User Existence

Distributed Data Federation without Disclosure of User Existence

m-Privacy for Collaborative Data Publishing

Methods to Mitigate Risk of Composition Attack in Independent Data Publications

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