Artificial Intelligence based Security Countermeasures for Internet of Things

This paper proposes a security model for protecting data on the Internet of Things (IoT) devices. This research work covers the challenges posed by IoT, including architecture problems, susceptibility to cyber-attacks, and data privacy concerns. To address these challenges, the paper suggests a security model that uses a combination of algorithms to protect against potential risks. The model will initiate the best-suited algorithm for a particular cyber-attack by using a machine learning algorithm. Probability will be used to decide which security algorithm to run, and this will be calculated from a database linked to the machine learning model. There are several security algorithms available, each with its pros and cons for different attacks. To determine the best algorithm for a specific cyber-attack, a variety of machine learning algorithms can be used. This paper aims to ensure data privacy and protection on IoT devices by using a sophisticated security model that addresses fundamental design issues, including security methods, privacy mechanisms, and data transformations. Overall, this study presents a viable strategy for IoT security that makes use of the most recent developments in cybersecurity and machine learning to protect against potential threats, ultimately resulting in a more secure and safe IoT ecosystem.