2008 · 186 citations · 21 references
EngineeringInformation SecurityInformation ForensicsPseudonymizationData ScienceData MiningData AnonymizationPrivacy SystemData IntegrationData ManagementTransaction DataKnowledge DiscoveryData PrivacyComputer SciencePrivacy AnonymityPrivacyData SecurityCryptographyData Mining ResearchTransaction DatabasesBig Data
This paper considers the problem of publishing "transaction data" for research purposes. Each transaction is an arbitrary set of items chosen from a large universe. Detailed transaction data provides an electronic image of one's life. This has two implications. One, transaction data are excellent candidates for data mining research. Two, use of transaction data would raise serious concerns over individual privacy. Therefore, before transaction data is released for data mining, it must be made anonymous so that data subjects cannot be re-identified. The challenge is that transaction data has no structure and can be extremely high dimensional. Traditional anonymization methods lose too much information on such data. To date, there has been no satisfactory privacy notion and solution proposed for anonymizing transaction data. This paper proposes one way to address this issue.
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Ashwin Machanavajjhala, Daniel Kifer, Johannes Gehrke et al. · ACM Transactions on Knowledge Discovery from Data · 2007 · 3.5K citations
Privacy Protection, Engineering, Privacy-preserving Techniques +17
L-diversity: privacy beyond k-anonymity
Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer et al. · 2006 · 2.4K citations
Privacy Protection, Engineering, Privacy-preserving Techniques +19