Machine Learning Vulnerability Assessment of Ring Oscillator Physical Unclonable Functions-Reference-Cited by-同舟云学术

Machine Learning Vulnerability Assessment of Ring Oscillator Physical Unclonable Functions

Published:2023-05-10 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Control, Automation and Diagnosis (ICCAD)
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Author:

Kareem Husam¹,Dunaev Dmitriy¹

Affiliation:

1. Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Department of Automation and Applied Informatics,Budapest,Hungary,H-1111

Funder

National Research, Development and Innovation Fund of Hungary

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10151847/10152298/10152413.pdf?arnumber=10152413

Reference21 articles.

1. Defense mechanism vulnerability analysis of ring oscillator PUFs against neural network modeling attacks using the dragonfly algorithm;ahmed;2020 IEEE International Conference on Electro Information Technology (EIT),0

2. Analysis and Machine Learning Vulnerability Assessment of XOR-Inverter based Ring Oscillator PUF Design

3. CT PUF: Configurable tristate PUF against machine learning attacks for IoT security;jiliang;IEEE Internet of Things Journal,2021

4. A machine learning attack resistant dual-mode PUF;qian;Proceedings of the 2018 on Great Lakes Symposium on VLSI,0

5. Matlab GUI-based Tool to Determine Performance Metrics of Physical Unclonable Functions

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