On private scalar product computation for privacy-preserving data mining
Information Security and Cryptology–ICISC 2004: 7th International Conference …, 2005•Springer
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 …
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 …
Abstract
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.
Springer