Machine Learning for Cyber Physical System: Advances and Challenges
暫譯: 機器學習在網絡物理系統中的應用:進展與挑戰

Nayak, Janmenjoy, Naik, Bighnaraj, S, Vimal

  • 出版商: Springer
  • 出版日期: 2025-04-12
  • 售價: $6,460
  • 貴賓價: 9.5$6,137
  • 語言: 英文
  • 頁數: 406
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3031540409
  • ISBN-13: 9783031540400
  • 相關分類: Machine Learning
  • 海外代購書籍(需單獨結帳)

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商品描述

This book provides a comprehensive platform for learning the state-of-the-art machine learning algorithms for solving several cybersecurity issues. It is helpful in guiding for the implementation of smart machine learning solutions to detect various cybersecurity problems and make the users to understand in combating malware, detect spam, and fight financial fraud to mitigate cybercrimes. With an effective analysis of cyber-physical data, it consists of the solution for many real-life problems such as anomaly detection, IoT-based framework for security and control, manufacturing control system, fault detection, smart cities, risk assessment of cyber-physical systems, medical diagnosis, smart grid systems, biometric-based physical and cybersecurity systems using advance machine learning approach. Filling an important gap between machine learning and cybersecurity communities, it discusses topics covering a wide range of modern and practical advance machine learning techniques, frameworks, and development tools to enable readers to engage with the cutting-edge research across various aspects of cybersecurity.

商品描述(中文翻譯)

本書提供了一個全面的平台,讓讀者學習最先進的機器學習演算法,以解決多種網路安全問題。它有助於指導實施智能機器學習解決方案,以檢測各種網路安全問題,並幫助用戶理解如何對抗惡意軟體、檢測垃圾郵件以及打擊金融詐騙,以減輕網路犯罪。透過對網路物理數據的有效分析,本書提供了許多現實生活問題的解決方案,例如異常檢測、基於物聯網的安全與控制框架、製造控制系統、故障檢測、智慧城市、網路物理系統的風險評估、醫療診斷、智慧電網系統,以及使用先進機器學習方法的生物識別物理和網路安全系統。本書填補了機器學習與網路安全社群之間的重要空白,討論了涵蓋現代和實用的先進機器學習技術、框架和開發工具的廣泛主題,使讀者能夠參與各種網路安全領域的前沿研究。

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