Helger Lipmaa's publications

On Private Scalar Product Computation for Privacy-Preserving Data Mining

Bart Goethals, Sven Laur, Helger Lipmaa and Taneli Mielikäinen. On Private Scalar Product Computation for Privacy-Preserving Data Mining. In Choonsik Park and Seongtaek Chee, editors, The 7th Annual International Conference in Information Security and Cryptology (ICISC 2004), volume 3506 of Lecture Notes in Computer Science, pages 104--120, Seoul, Korea, December 2--3, 2004. Springer, Heidelberg.

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In mining and integrating data from multiple sources, there are many privacy and security issues. In several different contexts, the security of the full privacy-preserving data mining protocol depends on the security of the underlying private scalar product protocol. We show that two of the private scalar product protocols, one of which was proposed in a leading data mining conference, are insecure. We then describe a provably private scalar product protocol that is based on homomorphic encryption and improve its efficiency so that it can also be used on massive datasets.

Keywords: Privacy-preserving data mining, private scalar product protocol, vertically partitioned frequent pattern mining.

More information: Publisher Webpage.

DOI: 10.1007/11496618_9


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