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Published byVirginia Elaine Payne Modified over 6 years ago
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A Privacy-Preserving Index for Range Queries
Bijit Hore, Sharad Mehrotra, Gene Tsudik Keiichi Shimamura
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Background Rise in use of cloud services
Outsourcing of IT infrastructure Increasing use of Database As a Service (DAS)
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Database as a Service Data is stored at service provider
Service provider cannot be trusted Security perimeter around data owner Client is secure and trusted Server (service provider) is not trusted
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Problem How to maintain security and privacy using DAS?
How to estimate and analyze the effectiveness of the solution?
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Solution Split the query into two parts
Insecure query that runs on the server Secure query that runs on the client Bucketization for range queries
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Encryption and Bucketization
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Tradeoff Larger buckets → more privacy
Smaller buckets → more performance Want: maximum privacy and performance Reality: tradeoff between privacy and performance
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Optimizing Buckets for Performance
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Breaking Bucketization
With knowledge of Bucketization scheme Probability distribution in each bucket the attacker can form statistical estimates of the values of attributes used in bucketization
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Protecting Against Attacks
Increase variance of values in a bucket More different values in each bucket weakens statistical estimates Increasing variance of one bucket lowers the variance of others Add entropy More values in each bucket weakens statistical estimates More rows are returned per bucket, decreasing performance
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Variance and Entropy
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Compromise Maximize variance and entropy for most privacy
Specify a maximum performance degradation Redistribute elements from “optimized buckets” to “composite buckets”
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Diffusion
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Precision Results
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Variance Results
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Entropy Results
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Privacy vs. Performance
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Conclusion Tradeoff between privacy and performance
Provides a solution for range queries that Maximizes privacy Limits performance degradation
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