Can I read Machine Learning Techniques for IoT Intrusions Detection in Aerospace Cyber-Physical Systems on EtoBox?

Machine Learning Techniques for IoT Intrusions Detection in Aerospace Cyber-Physical Systems by Yassine Maleh is a book available to read on EtoBox.

What is Machine Learning Techniques for IoT Intrusions Detection in Aerospace Cyber-Physical Systems about?

Aeronautical systems are no longer traditional masterpieces of autonomous mechanical engineering. Today, they are characterized by many intelligent technologies that include sensors, wireless standards and data analysis tools. Known as Aerospace Cyber-physical Systems (CPS), these CPSes are undergoing a massive transformation to increase the safety, efficiency and reliability of their operations. The physical system has created the Internet of Things IoT by integrating sensors, controllers and actuators. Nevertheless, the cyberspace of these aerospace CPSes offers many opportunities for malicious actors who threaten the security and privacy of vehicles/aircraft and their applications. Unprotected or poorly protected systems can easily be exploited for malicious purposes. Indeed, aerospace CPSes are always under threat from an increasing number of cyber-attacks through sensory or wireless channels, hardware, software or actuators. Recently, due to the significant advances and impressive results of machine learning techniques in the fields of image recognition, natural language processing and speech recognition for various longstanding artificial intelligence tasks, there has been a

Author

Yassine Maleh

Publisher

Springer International Publishing : Imprint: Springer

Published

2019

Language

EN

ISBN

9783030202149

Subjects

Engineering, Computer Science, Science