Hardware Trojans classification for gate-level netlists based on machine learning-Reference-Cited by-同舟云学术

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Hardware Trojans classification for gate-level netlists based on machine learning

Published:2016-07 Issue: Volume: Page:
ISSN:
Container-title:2016 IEEE 22nd International Symposium on On-Line Testing and Robust System Design (IOLTS)
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Author:

Hasegawa Kento,Oya Masaru,Yanagisawa Masao,Togawa Nozomu

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7589476/7604654/07604700.pdf?arnumber=7604700

Cited by 110 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. An Efficient ML-based Hardware Trojan Localization Framework for RTL Security Analysis;Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD;2024-09-09

2. A Siamese deep learning framework for efficient hardware Trojan detection using power side-channel data;Scientific Reports;2024-06-06

3. A Hardware Trojan Detection Method for Gate-Level Netlists Employing the CAMELOT Measure;2024 7th International Conference on Devices, Circuits and Systems (ICDCS);2024-04-23

4. FAST-GO: Fast, Accurate, and Scalable Hardware Trojan Detection using Graph Convolutional Networks;2024 25th International Symposium on Quality Electronic Design (ISQED);2024-04-03

5. Evaluation of Ensemble Learning Models for Hardware-Trojan Identification at Gate-level Netlists;2024 IEEE International Conference on Consumer Electronics (ICCE);2024-01-06

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