arXiv subjects

Beerendra Kumar

Publications and source records attributed to Beerendra Kumar.

4 recordsLinked to original sources

arXiv2010

A Distributed k-Secure Sum Protocol for Secure Multi-Party Computations

Secure sum computation of private data inputs is an interesting example of Secure Multiparty Computation (SMC) which has attracted many researchers to devise secure protocols with lower probability of data leakage. In this paper, we provide a novel protocol to compute the sum of individual data inputs with zero probability of data leakage when two neighbor parties collude to know the data of a middle party. We break the data block of each party into number of segments and redistribute the segments among parties before the computation. These entire steps create a scenario in which it becomes impossible for semi honest parties to know the private data of some other party.

cs.CR↗

arXiv2010

A Modified ck-Secure Sum Protocol for Multi-Party Computation

Secure Multi-Party Computation (SMC) allows multiple parties to compute some function of their inputs without disclosing the actual inputs to one another. Secure sum computation is an easily understood example and the component of the various SMC solutions. Secure sum computation allows parties to compute the sum of their individual inputs without disclosing the inputs to one another. In this paper, we propose a modified version of our ck-Secure Sum protocol with more security when a group of the computing parties conspire to know the data of some party.

cs.CR↗

arXiv2010

Changing Neighbors k Secure Sum Protocol for Secure Multi Party Computation

Secure sum computation of private data inputs is an important component of Secure Multi party Computation (SMC).In this paper we provide a protocol to compute the sum of individual data inputs with zero probability of data leakage. In our proposed protocol we break input of each party into number of segments and change the arrangement of the parties such that in each round of the computation the neighbors are changed. In this protocol it becomes impossible for semi honest parties to know the private data of some other party.

cs.CR↗

arXiv2009

Privacy Preserving k Secure Sum Protocol

Secure Multiparty Computation (SMC) allows parties to know the result of cooperative computation while preserving privacy of individual data. Secure sum computation is an important application of SMC. In our proposed protocols parties are allowed to compute the sum while keeping their individual data secret with increased computation complexity for hacking individual data. In this paper the data of individual party is broken into a fixed number of segments. For increasing the complexity we have used the randomization technique with segmentation

cs.CR↗