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Titlebook: Artificial Intelligence for Security; Enhancing Protection Tuomo Sipola,Janne Alatalo,Tero Kokkonen Book 2024 The Editor(s) (if applicable)

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發(fā)表于 2025-3-23 12:39:36 | 只看該作者
Stephen G. Sireci,Ella Banda,Craig S. Wellsapplication domains, including critical infrastructures. While these systems offer numerous benefits, they are vulnerable to cyberattacks that can physically harm individuals and damage the environment. Hence, securing CPS is a critical issue. In this context, artificial intelligence (AI) is playing
12#
發(fā)表于 2025-3-23 17:05:24 | 只看該作者
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發(fā)表于 2025-3-23 20:32:26 | 只看該作者
Ma ángeles Molina,Rocío Schettinily 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
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發(fā)表于 2025-3-23 22:25:49 | 只看該作者
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發(fā)表于 2025-3-24 06:08:17 | 只看該作者
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發(fā)表于 2025-3-24 08:20:00 | 只看該作者
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發(fā)表于 2025-3-24 12:59:52 | 只看該作者
Reference work 2018Latest editione the status of a software system. However, the large number of log entries makes manual analysis of the log data difficult. In order to identify errors or disruptions of computer systems at an early stage, an automated evaluation of the log data using artificial intelligence can be useful. In this
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發(fā)表于 2025-3-24 14:54:51 | 只看該作者
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發(fā)表于 2025-3-24 20:37:21 | 只看該作者
Martin E. R. Shanahan,Wulff Possarthis issue, we propose a novel hybrid intrusion detection algorithm that combines the deep autoencoder-based intrusion detection system (DAIDS) with recurrent neural networks (RNNs). The hybrid model aims to leverage the strengths of both approaches to enhance the accuracy and robustness of intrusion
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發(fā)表于 2025-3-25 00:56:38 | 只看該作者
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