Faculty of Information Technology, BUT

Publication Details

Efficient On-Chip Randomness Testing Utilizing Machine Learning Techniques

MRÁZEK Vojtěch, SEKANINA Lukáš, DOBAI Roland, SÝS Marek and ŠVENDA Petr. Efficient On-Chip Randomness Testing Utilizing Machine Learning Techniques. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 99, no. 99, pp. 1-11. ISSN 1063-8210.
Czech title
Efektivní na čipu implementované ověřování náhodnosti dat využívající technik strojového učení
Type
journal article
Language
english
Authors
Mrázek Vojtěch, Ing., Ph.D. (DCSY FIT BUT)
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY FIT BUT)
Dobai Roland, Ing., Ph.D. (DCSY FIT BUT)
Sýs Marek, Mgr., Ph.D. (FI MUNI)
Švenda Petr, Mgr. (FI MUNI)
Keywords
randomness testing, evolvable hardware, FPGA
Abstract
Randomness testing is an important procedure that bit streams, produced by critical cryptographic primitives such as encryption functions and hash functions, have to undergo. In this paper, a new hardware platform for randomness testing is proposed. The platform exploits the principles of genetic programming, which is a machine learning technique developed for automated program and circuit design. The platform is capable of evolving efficient randomness distinguishers directly on a chip. Each distinguisher is represented as a Boolean polynomial in the Algebraic Normal Form. Randomness testing is conducted for bit streams that are either stored in an on-chip memory or generated by a circuit placed on the chip. The platform is developed with a Xilinx Zynq-7000 All Programmable System on Chip which integrates a field programmable gate array with on-chip ARM processors. The platform is evaluated in terms of the quality of randomness testing, performance and resources utilization. With power budget less than 3 W, the platform provides comparable randomness testing capabilities with the standard testing batteries running on a personal computer.
Published
2019 (in print)
Pages
1-11
Journal
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 99, no. 99, ISSN 1063-8210
Publisher
IEEE Computer Society
DOI
BibTeX
@ARTICLE{FITPUB11687,
   author = "Vojt\v{e}ch Mr\'{a}zek and Luk\'{a}\v{s} Sekanina and Roland Dobai and Marek S\'{y}s and Petr \v{S}venda",
   title = "Efficient On-Chip Randomness Testing Utilizing Machine Learning Techniques",
   pages = "1--11",
   journal = "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
   volume = 99,
   number = 99,
   year = 2019,
   ISSN = "1063-8210",
   doi = "10.1109/TVLSI.2019.2923848",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11687"
}
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