Sin G. Teo

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An analysis of the accuracy and efficiency of multiparty secured protocols is carried out so that both measures can be optimally exploited in the design of malicious party and semi-honest party. Finding efficient protocols of the Secure Multiparty Computation(SMC) is one active research area in the field of privacy preserving data mining (PPDM). The(More)
Four main challenges (volume, velocity, variety, veracity) have confronted computation algorithm designers in big data mining. Homomorphic cryptosystem with secured multi-party computation of matrix operations has been shown to yield high privacy preserving while data miners perform information retrieval from big data. This research concerns with the(More)
Secure multi-party computation (SMC) allows parties to jointly compute a function over their inputs, while keeping every input confidential. It has been extensively applied in privacy-preserving computation, such as privacy-preserving data mining (PPDM), to protect data privacy. However, most SMC-based solutions are ad-hoc. They are proposed for specific(More)
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