Comprehensive Survey on AI-Based Technologies for Enhancing IoT Privacy and Security: Trends, Challenges, and Solutions

The Internet of Things (IoT) is revolutionizing modern technology by connecting numerous devices and applications. However, its lack of standardization has led to security and privacy challenges. Artificial intelligence (AI) techniques, such as machine learning, deep learning, and reinforcement learning, demonstrate the potential in addressing these issues by enabling the implementation of intrusion detection systems, authentication mechanisms, and privacy-preservation methods. We review various surveys and proposal papers that analyze different AI-based approaches to strengthen specific security requirements or counteract particular network threats or attacks. We identify novel trends in how AI methods are employed to detect threats and implement detection mechanisms for intrusion, anomalies, attacks, or malicious devices. Our primary contributions include the development of an IoT architecture that aids in identifying inherent privacy failures and security issues in IoT applications. Following this identification, we meticulously review the literature to gather diverse AI-based solutions that have been proposed and applied to address these specific IoT security and privacy issues. Our study provides a comprehensive understanding of the current AI methodologies in use and offers valuable insights for future research in this domain.