Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12258/3362
Title: Researches of algorithm of PRNG on the basis of bilinear pairing on points of an elliptic curve with use of a neural network
Authors: Chervyakov, N. I.
Червяков, Н. И.
Babenko, M. G.
Бабенко, М. Г.
Kucherov, N. N.
Кучеров, Н. Н.
Kuchukov, V. A.
Кучуков, В. А.
Shabalina, M. N.
Шабалина, М. Н.
Keywords: Bilinear pairing;Elliptic curve;Neural networks;Pseudo random number generator;Residue number system (RNS)
Issue Date: 2016
Publisher: Springer Verlag
Citation: Chervyakov, N.I., Babenko, M.G., Kucherov, N.N., Kuchukov, V.A., Shabalina, M.N. Researches of algorithm of PRNG on the basis of bilinear pairing on points of an elliptic curve with use of a neural network // Advances in Intelligent Systems and Computing. - 2016. - Volume 427. - Pages 167-173
Series/Report no.: Advances in Intelligent Systems and Computing
Abstract: In this paper pseudorandom number generator based on elliptic curve bilinear pairing is developed. Residue number system and approximate method are used for effictive realization of modular operations over finite field that allows to increase the speed of pseudorandom number generator for −256 by 2,15 times compared to similar PRNG that uses positional notation. The developed pseudorandom number generator based on neural network has as good statistical properties as random sequences from site random.org and passes Diehard tests
URI: https://www.scopus.com/record/display.uri?eid=2-s2.0-84958253822&origin=resultslist&sort=plf-f&src=s&nlo=1&nlr=20&nls=afprfnm-t&affilName=north+caucasus+federal+university&sid=4a5a00547f1a7b38888040771974d4c5&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=106&citeCnt=2&searchTerm=
http://hdl.handle.net/20.500.12258/3362
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