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

α
Dr. Atefeh Ghalambor Dezfuly
Dr. Atefeh Ghalambor Dezfuly
σ
Saeed Setayeshi
Saeed Setayeshi
ρ
Mohammad Mosleh
Mohammad Mosleh
Ѡ
Mohammad Kheyrandish
Mohammad Kheyrandish
α Islamic Azad University, Tehran Islamic Azad University, Tehran

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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. 1970. \u201cOptimal Rules Identification for a Random Number Generator Using Cellular Learning Automata\u201d. Unknown Journal GJCST Volume 12 (GJCST Volume 12 Issue 8): .

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v1.2

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April 21, 2012

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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.

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

Dr. Atefeh Ghalambor Dezfuly
Dr. Atefeh Ghalambor Dezfuly Islamic Azad University, Tehran
Saeed Setayeshi
Saeed Setayeshi
Mohammad Mosleh
Mohammad Mosleh
Mohammad Kheyrandish
Mohammad Kheyrandish

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