Optimal Rules Identification for a Random Number Generator Using Cellular Learning Automata

Optimal Rules Identification for a Random Number Generator Using Cellular Learning Automata

Dr. Atefeh Ghalambor Dezfuly * §

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Saeed Setayeshi

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Mohammad Mosleh

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kheyrandish

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§ Islamic Azad University

Optimal Rules Identification for a Random Number Generator Using Cellular Learning Automata

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Abstract

The cryptography is known as one of most essential ways for protecting information against threats. Among all encryption algorithms, stream ciphering can be indicated as a sample of swift ways for this purpose, in which, a generator is applied to produce a sequence of bits as the key stream. Although this sequence is seems to be random, severely, it contains a pattern that repeats periodically. Linear Feedback Shift Registers and cellular automata have been used as pseudo-random number generator. Some challenges such as error propagation and pattern dependability have motivated the designers to use CA for this purpose. The most important issue in using cellular automata includes determining an optimal set of rules for cells. This paper focuses on selecting optimal rules set for such this generator with using an open cellular learning automata, which is a cellular automata with learning capability and interacts with local and global environments.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Atefeh Ghalambor Dezfuly, Saeed Setayeshi, Mohammad Mosleh, kheyrandish. 1970. "Optimal Rules Identification for a Random Number Generator Using Cellular Learning Automata". Global Journal of Computer Science and Technology GJCST Volume 12 (GJCST Volume 12 Issue 8).

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GJCST Volume 12 Issue 8

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Cryptography global environment Learning Cellular Automata local environment stream ciphering Symmetric encryption

Submission ReceivedApril 13, 2012
Peer Review Double Blind
Handling Editor
Accepted May 3, 2012
Published May 15, 2012

Version of record

v1.2

Issue date

April 21, 2012

Language

English

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Article Matrices

Total Score: 129

Country: Iran

Subject: Global Journal of Computer Science and Technology

Authors: Dr. Atefeh Ghalambor Dezfuly, Saeed Setayeshi, Mohammad Mosleh, Mohammad Kheyrandish (PhD/Dr. count: 1)

View Count (all-time): 452

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Publish Date: 2012 01, Tue

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Total Views: 7.1K

Total Downloads: 325

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