The integration of Artificial Intelligence (AI) into various sectors presents both opportunities and challenges, particularly in the field of cyber security. AI has become a crucial tool in detecting and preventing cyber threats, offering new ways to protect industries, governments, and individuals. However, this same technology can be exploited to create more sophisticated and dangerous threats, raising concerns about data privacy, border surveillance, and the vulnerabilities of the Internet of Things (IoT). As AI and cyber security converge, it becomes essential to understand the dual nature of AI-its potential to both defend against and enable cyber-attacks.

Artificial Intelligence for Cyber Security and Industry 4.0 aims to provide a comprehensive overview of how AI is shaping the future of cyber security in the context of Industry 4.0. The book explores AI's role in enhancing cyber defense mechanisms, such as intrusion detection and data anonymization, while also addressing the risks posed by malicious AI applications. Key topics include cloud security, IoT vulnerabilities, and ethical concerns regarding weaponized AI. The book also delves into cutting-edge technologies like Quantum Machine Learning (QML) and AI-driven healthcare systems, offering a forward-looking perspective on the challenges and solutions in this rapidly evolving field.

Key Features:

Explores the dual role of AI in both strengthening and threatening cyber security in the context of Industry 4.0. Provides an in-depth analysis of AI-driven cyber security techniques, including machine learning-based intrusion detection and data anonymization. Investigates the malicious use of AI, addressing both expanded existing threats and the emergence of novel vulnerabilities. Discusses advanced software design for privacy preservation in big data environments. Covers the use of AI in specific security domains, such as border surveillance, healthcare, and the Internet of Things (IoT). Highlights AI applications in cloud security, data integrity, and privacy protection. Introduces Quantum Machine Learning (QML) algorithms and their relevance to cyber security. Explores the ethical concerns surrounding AI technologies, particularly in the context of weapon autonomy and border migration. Includes real-world scenarios and methodologies, bridging the gap between academic research and industry practice. Offers forward-looking insights into the role of AI in future cyber security challenges and solutions.