Engulf
发表于 2025-3-25 05:59:43
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SPALL
发表于 2025-3-25 11:00:25
Artificial Intelligence and Differential Privacy: Review of Protection Estimate Modelseoretical, and relational proof of privacy, which makes it important to understand the actual behavior of the DP-based protection models. For this purpose, we will review what kind of frameworks or models are available to estimate how well an implemented differential privacy model works. Special att
Mast-Cell
发表于 2025-3-25 14:26:50
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innovation
发表于 2025-3-25 19:54:34
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放逐某人
发表于 2025-3-25 23:04:30
Who Guards the Guardians? On Robustness of Deep Neural Networksther to mislead and change the model’s behavior or to leak information about the training data and potentially about the model in use. These attacks can be readily mapped within the Confidentiality, Integrity, and Availability triad components. We lay out the potential threat models and include the
中国纪念碑
发表于 2025-3-26 03:50:19
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无礼回复
发表于 2025-3-26 05:16:29
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唠叨
发表于 2025-3-26 09:07:24
On the Cybersecurity of Logistics in the Age of Artificial Intelligencely involved in national critical infrastructures (CI): transportation is directly identified as one of the CI sectors, and many other CI sectors cannot adequately function without properly working logistics. To optimize business processes and automate operational technology, different machine learni
Conflagration
发表于 2025-3-26 15:22:31
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Fulminate
发表于 2025-3-26 19:49:38
On Protection of the Next-Generation Mobile Networks Against Adversarial Examplesgent machine learning (ML)-driven network components to adversarial effects. Due to the shared nature of wireless mediums, these components may be susceptible to sophisticated attacks that can manipulate the training and inference processes of the AI/ML models over the air. In our research, we focus