Exploring Patterns and Assessing the Security of Pseudorandom Number Generators with Machine Learning

Sara Boancă

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Paper

Exploring Patterns and Assessing the Security of Pseudorandom Number Generators with Machine Learning

Topics: AI and Creativity; Deep Learning; Intelligence and Cybersecurity; Machine Learning; Neural Networks

In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, 186-193, 2024 , Rome, Italy

Author: Sara Boancă

Affiliation: Babeş-Bolyai University Cluj-Napoca, Romania

Keyword(s): Machine Learning, Neural Networks, Pattern Learning, Pseudorandom Number Generators.

Abstract: In recent years, Machine Learning methods have been employed for testing the security of pseudorandom number generators. It is considered that successful learning from pseudorandom data implies the existence of some detectable pattern within it, thus reducing the generator security. As the number and complexity of such approaches has reported important growth, the aim of the present paper is to synthesize current results, discuss perspectives and challenges and provide relevant guidelines for future study. To the best of our knowledge, this is the first comprehensive analysis on the current state of the research into the problem of pseudorandomness exploration by means of Machine Learning.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Boancă, S. (2024). Exploring Patterns and Assessing the Security of Pseudorandom Number Generators with Machine Learning. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 186-193. DOI: 10.5220/0012312900003636

@conference{icaart24,
author={Sara Boancă.},
title={Exploring Patterns and Assessing the Security of Pseudorandom Number Generators with Machine Learning},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={186-193},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012312900003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Exploring Patterns and Assessing the Security of Pseudorandom Number Generators with Machine Learning
SN - 978-989-758-680-4
IS - 2184-433X
AU - Boancă, S.
PY - 2024
SP - 186
EP - 193
DO - 10.5220/0012312900003636
PB - SciTePress