Title :
Transforming Semi-Honest Protocols to Ensure Accountability
Author :
Jiang, Wei ; Clifton, Chris
Author_Institution :
Purdue Univ., West Lafayette, IN
Abstract :
Secure multi-party computation (SMC) balances the use and confidentiality of distributed data. This is especially important for privacy-preserving data mining (PPDM). Most secure multi-party computation protocols are only proven secure under the semi-honest model, providing insufficient security for many PPDM applications. SMC protocols under the malicious adversary model generally have impractically high complexities for PPDM. We propose an accountable computing (AC) framework that enables liability for privacy compromise to be assigned to the responsible party without the complexity and cost of an SMC-protocol under the malicious model. We show how to transform a circuit-based semi-honest two-party protocol into a simple and efficient protocol satisfying the AC-framework
Keywords :
data mining; data privacy; protocols; ensure accountability; privacy preserving data mining; secure multiparty computation; semi honest protocols; Circuits; Computational modeling; Costs; Data mining; Data security; Distributed computing; Polynomials; Privacy; Protocols; Sliding mode control;
Conference_Titel :
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2702-7
DOI :
10.1109/ICDMW.2006.161