Hardware Trojan Detection Using Deep Learning-Generative Adversarial Network and Stacked Auto Encoder Neural Networks
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-5655-2_19
Reference17 articles.
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3. N. Kailash et al., An approach to detect and classify defects in cantilever beams using dynamic mode decomposition and machine learning. in Intelligent Manufacturing and Energy Sustainability (Springer, Singapore, 2020). pp. 731–738
4. R. Vishnupriya, M. Nirmala Devi, Hardware trojan detection using deep learning-deep stacked auto encoder. in Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications. (Springer, Singapore, 2021)
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1. A Siamese deep learning framework for efficient hardware Trojan detection using power side-channel data;Scientific Reports;2024-06-06
2. A Siamese Deep Learning Framework for Efficient Hardware Trojan Detection Using Power Side-Channel Data;2024-02-08
3. Hardware Trojan Detection Using Machine Learning: A Tutorial;ACM Transactions on Embedded Computing Systems;2023-04-19
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