Security and integrity in outsourcing of data mining

Outsourcing of data mining to an outside service provider brings important benefits to the data owner. These include (i) relief from the high mining cost, (ii) minimization of demands in resources, and (iii) effective centralized mining for multiple distributed owners. However, security and integrity are issues that must be tackled before enterprises can indeed outsource data mining task. The service provider should be prevented from accessing the actual data (security), and the results returned to the owner must be authentic (integrity). In this talk, we will first describe a model on the security and integrity problems in the outsourcing of data mining to a third party service provider. A recent result on secure association rules mining will be used to explain the outsourcing model and to illustrate the feasibility of an approach we used. In protecting the security in mining association rules, a substitution cipher technique was proposed in the encryption of transactional data. After identifying the non-trivial threats to a straightforward one-to-one item mapping substitution cipher, we propose a novel secure encryption algorithm based on a one-to-n item mapping that transforms transactions non-deterministically, yet guarantees correct decryption. We will also discuss the integrity problem in the same outsourcing model for association mining.