Enhanced Security of IoT Devices Using Ai Approach

Abstract

Internet of Things (IoT) connects various devices of networks, enhances services used to protect against attacks and provide privacy of the user related to all the types of security. This paper analyzes the methods and techniques used in IoT systems with artificial intelligence approach to enhance security. Applying AI algorithms to IoT security allows us to develop smart systems which can detect and block security attacks in real time. Due to the lack of powerful and unified security standards in IoT, an increasing number of IoT devices is vulnerable to threats from malicious attackers and bots. In order to detect attacks and identify abnormal behaviors of smart devices and networks, ML techniques can be used to overcome the issues and challenges. The IoT environment gathers data and analyzes it, and can be done effectively using machine learning, which has the ability to access data, analyze data, and perform decision-making based on data received from IoT devices. This paper addresses the issues which need to be investigated and addressed while implementing the machine learning schemes of security in IoT systems. Respectability, confirmation, and privacy are major principles to be considered to ensure the correspondence between IoT devices. AI offers us a new to solve traditional problems and help us reveal new insights on the field of IoT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.