Improving the Security and Usability of the Internet of Things through a Scalable Network-Level Smart System

Abstract

The Internet of Things (IoT) is a network of interconnected devices, sensors, and systems that communicate without human intervention. This technology involves embedded sensors, software, and wireless communication protocols that enable devices to collect and exchange data in real-time. This allows businesses and individuals to monitor and control various aspects of their environment, from temperature and humidity to security and energy consumption providing intelligent insights and automating various tasks. However, these increasingly connected devices bring security vulnerabilities to homes and businesses facing digital attacks that were never possible. These could be IoT-connected door locks that leak network passwords or IoT coffee makers that can be set to make coffee from outside one's home network. These problems arise mainly from IoT devices where usability and functionality were the focus, and security was not considered. Furthermore, these IoT devices cannot implement security due to limited storage, memory, and processing power. This paper aims to assess the feasibility and develop an intelligent system that improves the security of Internet of Things (IoT) devices in the best possible way with minimal user interaction and a learning curve, which the IoT manufacturer may need to provide. At the same time, the system will provide end users with traditional intrusion detection methods and artificial intelligence-driven detection techniques that monitor the IoT devices to get timely feedback and possible actions with or without users' interactions.