A Secured MultiParty Computational Protocol to Protect Cyber Space

In this paper, we show how our secured multiparty computation (SMC) protocols protect the data of an organization during the war from the cyberspace war when a large number of defense units interact with one another, while hiding the identity and computations done by them. SMC is a problem of inform...

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Vydané v:Information security journal. Ročník 19; číslo 4; s. 175 - 181
Hlavní autori: Mishra, Durgesh Kumar, Chandwani, Manohar
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Taylor & Francis Group 11.08.2010
Predmet:
Algorithms
Computation
Computer information security
correctness
Cryptography
cyberspace
Keys
Multilevel
Organizations
privacy
secure multiparty computation (SMC)
security
Sheet molding compounds
trusted third party (TTP)
ISSN:1939-3555, 1939-3547
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Shrnutí:In this paper, we show how our secured multiparty computation (SMC) protocols protect the data of an organization during the war from the cyberspace war when a large number of defense units interact with one another, while hiding the identity and computations done by them. SMC is a problem of information security when large organizations interact with one another for huge data sharing and data exchange. It is quite possible that during sharing and exchange, the private data also get hacked. In order to protect and secure the private data, the protocols of SMC need to be deployed in the large computer networks on which the organizations work. The protocols work at the micro-level in terms of cryptography with which the data are encrypted and then shared, while allowing the keys to be used for sharable data while also keeping the keys untouched for private data. At the macro level, multilevel architectures are used for different types of security to be achieved. The computation part of the secured multiparty computation is based on the algorithmic complexity theory. The algorithms realize the protocols in such a way that it is tedious to break (decrypt) the keys to hack the private data.
Bibliografia:ObjectType-Article-2
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ISSN:1939-3555
1939-3547
DOI:10.1080/19393550903532553