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Titlebook: Handbook of Big Data Analytics and Forensics; Kim-Kwang Raymond Choo,Ali Dehghantanha Book 2022 Springer Nature Switzerland AG 2022 cyber

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發(fā)表于 2025-3-21 19:24:43 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Handbook of Big Data Analytics and Forensics
編輯Kim-Kwang Raymond Choo,Ali Dehghantanha
視頻videohttp://file.papertrans.cn/421/420871/420871.mp4
概述Covers advances in big data analytics and digital forensics from an interdisciplinary lens.Provides a comprehensive review and bibliometric analysis of big data and IoT applications, as well as future
圖書封面Titlebook: Handbook of Big Data Analytics and Forensics;  Kim-Kwang Raymond Choo,Ali Dehghantanha Book 2022 Springer Nature Switzerland AG 2022 cyber
描述.This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The?authors?propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes?a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the?sixth?chapter.? ?.The?authors?evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook a
出版日期Book 2022
關(guān)鍵詞cyber threat; cyber security; privacy; big data; threat intelligence; machine learning; cyber forensics; in
版次1
doihttps://doi.org/10.1007/978-3-030-74753-4
isbn_softcover978-3-030-74755-8
isbn_ebook978-3-030-74753-4
copyrightSpringer Nature Switzerland AG 2022
The information of publication is updating

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發(fā)表于 2025-3-21 22:17:26 | 只看該作者
Die Erythema multiforme-Gruppe,ontemporary approaches and techniques, including those based on machine and deep learning. A number of research challenges and opportunities are also presented in the book, which hopefully will motivate further research in this area.
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analysis of big data and IoT applications, as well as future.This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT s
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發(fā)表于 2025-3-23 08:10:21 | 只看該作者
,Erkrankungen der endokrinen Drüsen,ccuracy rate and 0% false-negative and false-positive rates. The true-positive and true-negative rates were both 100%. These results show that adaptive neural trees borrow from deep neural networks and decision trees to deliver exceptional results.
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