Testing Cryptographically Secure Pseudo Random Number Generators with Artificial Neural Networks-Reference-Cited by-同舟云学术

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Testing Cryptographically Secure Pseudo Random Number Generators with Artificial Neural Networks

Published:2018-08 Issue: Volume: Page:
ISSN:
Container-title:2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
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Author:

Fischer Tilo

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8454845/8455868/08456037.pdf?arnumber=8456037

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic Physical Unclonable Function Relying on Lasing Polarization;ACS Photonics;2024-06-05

2. Low-complexity Machine Learning Architecture for Hardware-aware True Random Number Generators Assessment and Continuous Monitoring;2023 18th Conference on Ph.D Research in Microelectronics and Electronics (PRIME);2023-06-18

3. Learned pseudo-random number generator: WGAN-GP for generating statistically robust random numbers;PLOS ONE;2023-06-14

4. Tunable Key-Size Physical Unclonable Functions Based on Phase Segregation in Mixed Halide Perovskites;ACS Applied Materials & Interfaces;2023-05-04

5. A resource efficient pseudo random number generator based on sawtooth maps for Internet of Things;SECURITY AND PRIVACY;2023-02-26

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