Sharemind: A Framework for Fast Privacy-Preserving Computations

Gathering and processing sensitive data is a difficult task. In fact, there is no common recipe for building the necessary information systems. In this paper, we present a provably secure and efficient general-purpose computation system to address this problem. Our solution-- Sharemind --is a virtual machine for privacy-preserving data processing that relies on share computing techniques. This is a standard way for securely evaluating functions in a multi-party computation environment. The novelty of our solution is in the choice of the secret sharing scheme and the design of the protocol suite. We have made many practical decisions to make large-scale share computing feasible in practice. The protocols of Sharemind are information-theoretically secure in the honest-but-curious model with three computing participants. Although the honest-but-curious model does not tolerate malicious participants, it still provides significantly increased privacy preservation when compared to standard centralised databases.

[1]  Andrew Chi-Chih Yao,et al.  How to generate and exchange secrets , 1986, 27th Annual Symposium on Foundations of Computer Science (sfcs 1986).

[2]  J'anos Simon,et al.  Proceedings of the twentieth annual ACM symposium on Theory of computing , 1988, STOC 1988.

[3]  Avi Wigderson,et al.  Completeness theorems for non-cryptographic fault-tolerant distributed computation , 1988, STOC '88.

[4]  David Chaum,et al.  Multiparty Unconditionally Secure Protocols (Extended Abstract) , 1988, STOC.

[5]  Eyal Kushilevitz,et al.  A zero-one law for Boolean privacy , 1989, STOC '89.

[6]  Leonid A. Levin,et al.  Fair Computation of General Functions in Presence of Immoral Majority , 1990, CRYPTO.

[7]  Ran Canetti,et al.  Asynchronous secure computation , 1993, STOC.

[8]  Tal Rabin,et al.  Asynchronous secure computations with optimal resilience (extended abstract) , 1994, PODC '94.

[9]  C. Moler,et al.  Advances in Cryptology , 2000, Lecture Notes in Computer Science.

[10]  Ramakrishnan Srikant,et al.  Privacy-preserving data mining , 2000, SIGMOD '00.

[11]  Ran Canetti,et al.  Security and Composition of Multiparty Cryptographic Protocols , 2000, Journal of Cryptology.

[12]  Silvio Micali,et al.  Parallel Reducibility for Information-Theoretically Secure Computation , 2000, CRYPTO.

[13]  Ueli Maurer,et al.  Player Simulation and General Adversary Structures in Perfect Multiparty Computation , 2000, Journal of Cryptology.

[14]  Charu C. Aggarwal,et al.  On the design and quantification of privacy preserving data mining algorithms , 2001, PODS.

[15]  Wenliang Du,et al.  Protocols for Secure Remote Database Access with Approximate Matching , 2001, E-Commerce Security and Privacy.

[16]  Ran Canetti,et al.  Universally composable security: a new paradigm for cryptographic protocols , 2001, Proceedings 2001 IEEE International Conference on Cluster Computing.

[17]  Alexandre V. Evfimievski,et al.  Privacy preserving mining of association rules , 2002, Inf. Syst..

[18]  Yuval Ishai,et al.  Efficient Multi-party Computation over Rings , 2003, EUROCRYPT.

[19]  Yehuda Lindell,et al.  On the Limitations of Universally Composable Two-Party Computation without Set-up Assumptions , 2003, EUROCRYPT.

[20]  Yehuda Lindell,et al.  A Proof of Yao's Protocol for Secure Two-Party Computation , 2004, Electron. Colloquium Comput. Complex..

[21]  Benny Pinkas,et al.  Fairplay - Secure Two-Party Computation System , 2004, USENIX Security Symposium.

[22]  Donald Beaver,et al.  Secure multiparty protocols and zero-knowledge proof systems tolerating a faulty minority , 2004, Journal of Cryptology.

[23]  Benny Pinkas,et al.  Fairplay - Secure Two-Party Computation System (Awarded Best Student Paper!) , 2004 .

[24]  Eike Kiltz,et al.  Unconditionally Secure Constant Round Multi-Party Computation for Equality, Comparison, Bits and Exponentiation , 2006, IACR Cryptol. ePrint Arch..

[25]  Ivan Damgård,et al.  A Practical Implementation of Secure Auctions Based on Multiparty Integer Computation , 2006, Financial Cryptography.

[26]  Rebecca N. Wright,et al.  Experimental analysis of a privacy-preserving scalar product protocol , 2006, Comput. Syst. Sci. Eng..