Randomness testing and comparison of classical and quantum bit generators

Boztas, S and Burton, B 2017, 'Randomness testing and comparison of classical and quantum bit generators', in Proceedings of 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, Crete, 3-6 July 2017, pp. 1029-1032.


Document type: Conference Paper
Collection: Conference Papers

Title Randomness testing and comparison of classical and quantum bit generators
Author(s) Boztas, S
Burton, B
Year 2017
Conference name 2017 IEEE Symposium on Computers and Communications (ISCC)
Conference location Heraklion, Crete
Conference dates 3-6 July 2017
Proceedings title Proceedings of 2017 IEEE Symposium on Computers and Communications (ISCC)
Publisher IEEE
Place of publication USA
Start page 1029
End page 1032
Total pages 3
Abstract Randomness is crucial to enabling secure and robust communications. Ideally one should harness high entropy physical processes, but this is difficult so pseudorandomness is usually substituted for randomness. We introduce improved complexity randomness tests and use them to judge three pseudorandom bit generators; the AES block cipher (standard, strongly believed to be secure), the Dragon stream cipher (eStream finalist), and the GNU C library function rand(). We also test the output from a quantum random bit generator (QRBG). While the two ciphers can easily be distinguished from the much inferior rand(), the output statistics of the two classical generators are similar to that of the QRBG, and both provide high-quality pseudorandom bits.
Subjects Coding and Information Theory
Data Structures
Keyword(s) Randomness testing
information theory
algorithms
DOI - identifier 10.1109/ISCC.2017.8024660
Copyright notice © Copyright 2019 IEEE - All rights reserved
ISBN 978-1-5386-1629-1
ISSN 15301346
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 0 times in Scopus Article
Altmetric details:
Access Statistics: 27 Abstract Views  -  Detailed Statistics
Created: Mon, 18 Dec 2017, 09:53:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us