The EC sequences on points of an elliptic curve realization using neural networks
This paper shows that pseudorandom number generator based on ECsequence doesn’t satisfy the condition of Knuth k-distribution. A modified pseudorandom number generator on elliptic curve points built in neural network basis is proposed. The proposed generator allows to improve statistical properties...
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| Médium: | Статья |
| Jazyk: | English |
| Vydáno: |
Springer Verlag
2018
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| On-line přístup: | https://www.scopus.com/record/display.uri?eid=2-s2.0-84958260764&origin=resultslist&sort=plf-f&src=s&nlo=1&nlr=20&nls=afprfnm-t&affilName=north+caucasus+federal+university&sid=94a185ef2a894025076dc32df599dd02&sot=afnl&sdt=cl&cluster=scopubyr%2c%222016%22%2ct&sl=53&s=%28AF-ID%28%22North+Caucasus+Federal+University%22+60070541%29%29&relpos=95&citeCnt=2&searchTerm= https://dspace.ncfu.ru/handle/20.500.12258/3335 |
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| Shrnutí: | This paper shows that pseudorandom number generator based on ECsequence doesn’t satisfy the condition of Knuth k-distribution. A modified pseudorandom number generator on elliptic curve points built in neural network basis is proposed. The proposed generator allows to improve statistical properties of the sequence based on elliptic curve points so that it satisfies the condition of kdistribution i.e. the sequence is pseudorandom. Application of Neural network over a finite ring to arithmetic operations over finite field allows to increase the speed of pseudorandom number generator on elliptic curve points EC-256 by 1,73 times due to parallel structure |
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