Description
Book SynopsisThis book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications.
Table of Contents1. Introduction to AI and Cyber security for industry
2. AI for Industrial automation using Cyber security
3. Applying deep learning and cyber security in medical industry
4. Intelligent Autonomous Drones in industry 4.0
5. AI and IOT security for manufacturing industry
6. Intelligent methods for analysing and correlating log
7. AI Driven vehicle security
8. Applying machine learning techniques and tools for malware analysis in IT industry
9. Intelligent methods for profiling threat and adversary
10. Edge /fog/cloud computing for AI based security services
11. Artificial intelligence based cyber security applications
12. Next Generation Challenges and Future in AI and Cybersecurity in industry 4.0
