A Study on Artificial Intelligence-based Security Techniques for IoT-based Systems

In a recent scenario, the Internet of Things (IoT) enables the Integration of disparate home automation systems into a unified network that can be managed from a single device, such as a smartphone. Connections to the Internet that aren't secure: A lack of security standards may make the Internet of Things devices vulnerable to assault, including hacking. Though current designs may address some security concerns inherent to the Internet of Things, most solutions suffer from two significant flaws. This only addresses a single threat at the level of IoT-edge architecture and cannot be expanded to deal with new threats as misunderstood obstacles. Second, its core operations are trustworthy and seldom require additional hardware to implement the advised security measures. The AI-SM-IoT framework is a three-tiered system incorporating security components based on AI motors into every IoT stack that communicates with the network's edge. AI motors were also added as a new transmission layer. This study suggests an AI-based security method for IoT environments (AI-SM-IoT system). This concept was based on the periphery of a network of AI-enabled security components for IoT disaster preparedness. The architecture recommends three main modules: cyber threat searching, intelligent firewalls for online applications, and cybercrime information. Based on the idea of the "cyberspace killing chain," the modules given detect, identify, and continue to identify the stage of an assault life cycle. It describes each long-term security in the suggested framework and demonstrates its usefulness in applications facing various risks. A distinct layer of AI-SM-IoT services is used to deliver artificial intelligence (AI) safety modules to address each risk in the boundaries layer. The architectural freedom from the project's essential regions and comparatively low latency, which offers safety as a service rather than an embedded network edge on the Internet of Things design, contrasted with the system framework's earlier designs. Based on the administration score of the IoT platform, throughput, security, and working time, it evaluated the proposed method.