MacLeR: machine learning-based runtime hardware trojan detection in resource-constrained IoT edge devices
Traditional learning-based approaches for runtime hardware Trojan (HT) detection require
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
MacLeR: Machine Learning-Based Runtime Hardware Trojan Detection in Resource-Constrained IoT Edge Devices
F Khalid, SR Hasan, S Zia, O Hasan… - … on Computer-Aided …, 2020 - nchr.elsevierpure.com
Traditional learning-based approaches for runtime hardware Trojan (HT) detection require
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
MacLeR: Machine Learning-Based Runtime Hardware Trojan Detection in Resource-Constrained IoT Edge Devices
F Khalid, SR Hasan, S Zia, O Hasan… - … on Computer-Aided …, 2020 - research.uaeu.ac.ae
Traditional learning-based approaches for runtime hardware Trojan (HT) detection require
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
[PDF][PDF] MacLeR: Machine Learning-based Run-Time Hardware Trojan Detection in Resource-Constrained IoT Edge Devices
F Khalid, SR Hasan, S Zia, O Hasan - Power - academia.edu
Traditional learning-based approaches for run-time Hardware Trojan detection require
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
[引用][C] MacLeR: Machine Learning-Based Runtime Hardware Trojan Detection in Resource-Constrained IoT Edge Devices
F Khalid, SR Hasan, S Zia, O Hasan… - … on Computer-Aided …, 2020 - repositum.tuwien.at
reposiTUm: MacLeR: Machine Learning-Based Runtime Hardware Trojan Detection in
Resource-Constrained IoT Edge Devices reposiTUm ABOUT REPOSITUM HELP Login …
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MacLeR: Machine Learning-based Run-Time Hardware Trojan Detection in Resource-Constrained IoT Edge Devices
F Khalid, S Rafay Hasan, S Zia, O Hasan… - arXiv e …, 2020 - ui.adsabs.harvard.edu
Traditional learning-based approaches for run-time Hardware Trojan detection require
complex and expensive on-chip data acquisition frameworks and thus incur high area and …
complex and expensive on-chip data acquisition frameworks and thus incur high area and …
MacLeR: Machine Learning-Based Runtime Hardware Trojan Detection in Resource-Constrained IoT Edge Devices
F Khalid, SR Hasan, S Zia, O Hasan… - … on Computer-Aided …, 2020 - nyuscholars.nyu.edu
Traditional learning-based approaches for runtime hardware Trojan (HT) detection require
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
complex and expensive on-chip data acquisition frameworks, and thus incur high area and …
MacLeR: Machine Learning-based Run-Time Hardware Trojan Detection in Resource-Constrained IoT Edge Devices
F Khalid, SR Hasan, S Zia, O Hasan, F Awwad… - arXiv preprint arXiv …, 2020 - arxiv.org
Traditional learning-based approaches for run-time Hardware Trojan detection require
complex and expensive on-chip data acquisition frameworks and thus incur high area and …
complex and expensive on-chip data acquisition frameworks and thus incur high area and …