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Titlebook: Explainable AI for Cybersecurity; Zhixin Pan,Prabhat Mishra Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive lic

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樓主: Ensign
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發(fā)表于 2025-3-23 13:34:39 | 只看該作者
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發(fā)表于 2025-3-24 01:15:44 | 只看該作者
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發(fā)表于 2025-3-24 05:44:08 | 只看該作者
The Future of AI-Enabled Cybersecurity of vulnerability detection and mitigation methods using explainable AI. This chapter concludes the book with a summary of ideas presented in the previous chapters and outlines the road map of future cybersecurity challenges and opportunities.
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發(fā)表于 2025-3-24 07:59:17 | 只看該作者
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發(fā)表于 2025-3-24 11:20:30 | 只看該作者
Siamak Talatahari,Hadi Bayzidi,Mehdi Bayzidiate Arrays (FPGA) and Graphic Processing Units (GPU). Hardware acceleration enables fast and efficient explainable AI models that provide explainability as well as applicability across diverse domains, including real-time and safety-critical systems.
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發(fā)表于 2025-3-24 18:03:50 | 只看該作者
Mary M. Eshaghian-Wilner,Lili Haital evaluation demonstrates that the proposed approach deployed on TPU can provide drastic improvement in interpretation time (39x on average) as well as energy efficiency (69x on average) compared to existing acceleration techniques.
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發(fā)表于 2025-3-24 22:14:28 | 只看該作者
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發(fā)表于 2025-3-25 02:30:19 | 只看該作者
Hardware Acceleration of Explainable AIate Arrays (FPGA) and Graphic Processing Units (GPU). Hardware acceleration enables fast and efficient explainable AI models that provide explainability as well as applicability across diverse domains, including real-time and safety-critical systems.
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