Abolfazl Omidi - Bachelor student of computer engineering, Poldokhtar Institute of higher education Lorestan, Iran

This paper provides an overview of the use of machine learning (ML) techniques for Internet of Things (IoT) security. The IoT refers to a network of interconnected devices that can communicate, collect data, and make decisions with minimal human intervention. However, the proliferation of IoT devices has raised concerns about their security, as hackers can exploit vulnerabilities to gain unauthorized access, steal sensitive information, and launch attacks. ML is a subset of artificial intelligence that enables systems to learn from data, identify patterns, and make decisions without explicit programming. The use of ML in IoT security can help detect anomalies, predict attacks, and develop dynamic defenses.The paper draws insights from various resources, including seven books, that cover topics on practical cryptography for the IoT, securing IoT devices and networks, and machine learning algorithms for cybersecurity. The authors present an overview of IoT security and the challenges involved in ensuring the privacy and security of data. They introduce the concept of ML and how it can be leveraged to offer solutions to critical problems such as cybersecurity in IoT environments, ۵G, and smart cities.The paper further explores specific resources that examine the use of cryptographic techniques, guide to securing IoT devices and networks, and algorithms used in protecting systems with data. Additionally, the paper highlights the importance of information security and cryptology in the modern era and the rise of new technologies such as IoT. Finally, the authors discuss the relevance of the book "Artificial Intelligence and Machine Learning for Business" to IoT security, particularly in the context of business applications. They explore how ML can be used to improve business performance, detect fraud, and enhance customer experiences. In conclusion, the paper provides a comprehensive overview of the use of ML techniques for IoT security and highlights insights from various resources.

IoT security, Machine learning, Cryptography, Cybersecurity , Artificial intelligence