A unified approach for multilevel database security based on inference engines
SIGCSE '89 Proceedings of the twentieth SIGCSE technical symposium on Computer science education
Adaptively secure multi-party computation
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A practical approach to solve Secure Multi-party Computation problems
Proceedings of the 2002 workshop on New security paradigms
Privacy-Preserving Cooperative Scientific Computations
CSFW '01 Proceedings of the 14th IEEE workshop on Computer Security Foundations
Secure and private sequence comparisons
Proceedings of the 2003 ACM workshop on Privacy in the electronic society
The role of cryptography in database security
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Private collaborative forecasting and benchmarking
Proceedings of the 2004 ACM workshop on Privacy in the electronic society
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
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In this paper, we propose a new Virtual Party Protocol (VPP) protocol for Secure Multi-Party Computation (SMC). There are many computations and surveys which involve confidential data from many parties or organizations. As the concerned data is property of the organization or the party, preservation and security of this data is of prime importance for such type of computations. Although the computation requires data from all the parties, but none of the associated parties would want to reveal their data to the other parties. We have proposed a new protocol to perform computation on encrypted data. The data is encrypted in a manner that it does not affect the result of the computation. It uses modifier tokens which are distributed among virtual parties, and finally used in the computation. The computation function uses the acquired data and modifier tokens to compute right result from the encrypted data. Thus without revealing the data, right result can be computed and privacy of the parties is maintained. We have given a probabilistic security analysis and have also shown how we can achieve zero hacking security with proper configuration.