arXiv subjects

Durgesh Kumar Mishra

Publications and source records attributed to Durgesh Kumar Mishra.

6 recordsLinked to original sources

arXiv2014

Simulation of Collision Resistant Secure Sum Protocol

secure multi-party computation is widely studied area in computer science. It is touching all most every aspect of human life. This paper demonstrates theoretical and experimental results of one of the secure multi-party computation protocols proposed by Shukla et al. implemented using visual C++. Data outflow probability is computed by changing parameters. At the end, time and space complexity is calculated using theoretical and experimental results.

cs.CR↗

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

Multi-Agent Model using Secure Multi-Party Computing in e-Governance

Information management and retrieval of all the citizen occurs in almost all the public service functions. Electronic Government system is an emerging trend in India through which efforts are made to strive maximum safety and security. Various solutions for this have been proposed like Shibboleth, Public Key Infrastructure, Smart Cards and Light Weight Directory Access Protocols. Still, none of these guarantee 100 percent security. Efforts are being made to provide common national identity solution to various diverse Government identity cards. In this paper, we discuss issues related to these solutions.

cs.MA↗

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↗