2018 · 12 citations · 27 references
ComputingComputer ScienceInformation TechnologyComputer SecurityData MiningDatabasesData AnonymizationData ConfidentialityData PrivacyData SecurityDatabase PrivacyDatabase SecurityAdversary ModelAnonymizationAnonymization RiskLinkage AttacksPrivacyPrivacy-preserving DatabasesSensitive Data AnonymizationUtility-privacy Tradeoff
Set-valued database publication has been attracting much attention due to its benefit for various applications like recommendation systems and marketing analysis. However, publishing original database directly is risky since an unauthorized party may violate individual privacy by associating and analyzing relations between individuals and set of items in the published database, which is known as identity linkage attack. Generally, an attack is performed based on attacker's background knowledge obtained by a prior investigation and such adversary knowledge should be taken into account in the data anonymization. Various data anonymization schemes have been proposed to prevent the identity linkage attack. However, in existing data anonymization schemes, either data utility or data property is reduced a lot after excessive database modification and consequently data recipients become to distrust the released database.
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Mining frequent patterns without candidate generation
Jiawei Han, Jian Pei, Yiwen Yin · ACM SIGMOD Record · 2000 · 6.4K citations
Ashwin Machanavajjhala, Daniel Kifer, Johannes Gehrke et al. · ACM Transactions on Knowledge Discovery from Data · 2007 · 3.6K citations
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
Ninghui Li, Tiancheng Li, Suresh Venkatasubramanian · 2007 · 3.4K citations