loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Marek Sýs ; Dušan Klinec and Petr Švenda

Affiliation: Masaryk University, Czech Republic

Keyword(s): Statistical Randomness Testing, Hypothesis Testing, Boolean Function.

Related Ontology Subjects/Areas/Topics: Applied Cryptography ; Cryptographic Techniques and Key Management ; Data and Application Security and Privacy ; Data Engineering ; Data Protection ; Databases and Data Security ; Information and Systems Security ; Security Verification and Validation

Abstract: The wide range of security applications requires data either truly random or indistinguishable from random. The statistical tests included in batteries such as NIST STS or Dieharder are frequently used to assess the randomness property. We designed a principally simple, yet powerful, statistical randomness test working on bit level. It is based on a search for boolean function(s) indicating a bias when applied to the tested stream not expected for truly random data. The deviances are detected in seconds rather than tens of minutes required by the common batteries. Importantly, the boolean function indicating the bias directly describes the pattern responsible for this bias. This allows to construct the bit predictor or to fix the cause of bias in the function design. The present bias is typically detected in at least an order of magnitude less data than required by NIST STS or Dieharder. The tests included in these batteries are either too simple to spot the common biases (like the M onobit test) or overly complex (like the Fourier Transform test) requiring an extensive amount of data. The proposed approach called BoolTest fills this gap. The performance was verified on more than 20 real world cryptographic functions – block and stream ciphers, hash functions and pseudorandom generators. Among others, the previously unknown bias in the output of C rand() and Java Random generators was found. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.207.240.205

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Sýs, M.; Klinec, D. and Švenda, P. (2017). The Efficient Randomness Testing using Boolean Functions. In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - SECRYPT; ISBN 978-989-758-259-2; ISSN 2184-3236, SciTePress, pages 92-103. DOI: 10.5220/0006425100920103

@conference{secrypt17,
author={Marek Sýs. and Dušan Klinec. and Petr Švenda.},
title={The Efficient Randomness Testing using Boolean Functions},
booktitle={Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - SECRYPT},
year={2017},
pages={92-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006425100920103},
isbn={978-989-758-259-2},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - SECRYPT
TI - The Efficient Randomness Testing using Boolean Functions
SN - 978-989-758-259-2
IS - 2184-3236
AU - Sýs, M.
AU - Klinec, D.
AU - Švenda, P.
PY - 2017
SP - 92
EP - 103
DO - 10.5220/0006425100920103
PB - SciTePress