Evaluation on Hardware-Trojan Detection at Gate-Level IP Cores Utilizing Machine Learning Methods

Author:

Kurihara Tatsuki,Hasegawa Kento,Togawa Nozomu

Publisher

IEEE

Cited by 18 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. Accurate Hardware Trojan Detection Technology Based on Node Concealment Features;2024 IEEE International Test Conference in Asia (ITC-Asia);2024-08-18

2. 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

3. A fine-grained detection method for gate-level hardware Trojan base on bidirectional Graph Neural Networks;Journal of King Saud University - Computer and Information Sciences;2023-12

4. A unioned graph neural network based hardware Trojan node detection;IEICE Electronics Express;2023-07-10

5. A Cost-Driven Method for Deep-Learning-Based Hardware Trojan Detection;Sensors;2023-06-11

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