Minutes 发表于 2025-3-25 06:01:42

2191-5768 ion is not only a challenging problem, but there are also problems in performing such research, particularly in obtaining relevant data. This SpringerBrief desc978-3-319-73787-4978-3-319-73788-1Series ISSN 2191-5768 Series E-ISSN 2191-5776

bifurcate 发表于 2025-3-25 10:33:18

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prosperity 发表于 2025-3-25 11:44:39

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持续 发表于 2025-3-25 16:46:51

https://doi.org/10.1007/978-3-319-73788-1Cyber security; Cyber attribution; Cyber attacks; Artificial intelligence; Argumentation; Machine Learnin

压碎 发表于 2025-3-25 23:26:48

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Immunoglobulin 发表于 2025-3-26 02:01:30

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袭击 发表于 2025-3-26 04:40:33

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Myofibrils 发表于 2025-3-26 12:15:19

https://doi.org/10.1007/978-3-031-14649-7tack. In this chapter, we leverage the dataset from the capture-the-flag event held at DEFCON discussed in Chap. ., and propose . model comprised solely of the AM (that is, without probabilistic information) designed to aid an analyst in attributing a cyberattack. We build models from latent variabl

Scintigraphy 发表于 2025-3-26 13:55:22

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轻率的你 发表于 2025-3-26 17:59:00

https://doi.org/10.1007/978-3-031-14649-7lity of standard machine learning models to identify the actor as demonstrated in Chap. .. Structured argumentation-based frameworks like DeLP can help alleviate deception to some extent by providing arguments for the selection of a particular actor/actors responsible for the attack based on the evi
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查看完整版本: Titlebook: Artificial Intelligence Tools for Cyber Attribution; Eric Nunes,Paulo Shakarian,Andrew Ruef Book 2018 The Author(s) 2018 Cyber security.Cy