AC-Framework for Privacy-Preserving Collaboration

The secure multi-party computation (SMC) model provides means for balancing the use and confidentiality of distributed data. Increasing security concerns have led to a surge in work on practical secure multi-party computation protocols. However, most are only proven secure under the semihonest model, and security under this adversary model is insufficient for most applications in the field of privacypreserving data mining. In this paper, we present the full spectrum of the accountable computing (AC) framework, which is sufficient or practical for many applications without the complexity and cost of an SMC-protocol under the malicious model. Furthermore, to show the applicability of the AC-framework, we present an application under this framework regarding privacy-preserving mining frequent itemsets.

• Type: Conference
• Year: 2007
• Where: SDM
• Authors: Wei Jiang, Chris Clifton
• Keywords: Data Mining, Model Provides Means, Multi-party Computation Protocols, SDM 2007, Secure Multi-party Computation