Machine Learning for Cyber Physical System: Advances and Challenges: 60

Machine Learning for Cyber Physical System: Advances and Challenges: 60 book cover

Machine Learning for Cyber Physical System: Advances and Challenges: 60

Author(s): Janmenjoy Nayak (Editor), Bighnaraj Naik (Editor), Vimal S (Editor), Margarita Favorskaya (Editor)

  • Publisher: Springer
  • Publication Date: 12 April 2025
  • Language: English
  • Print length: 422 pages
  • ISBN-10: 3031540409
  • ISBN-13: 9783031540400

Book Description

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.

Editorial Reviews

From the Back Cover

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.

View on Amazon

电子书代发PDF格式价格30我要求助
未经允许不得转载:Wow! eBook » Machine Learning for Cyber Physical System: Advances and Challenges: 60