Introspecting diverse IoT-traffic analysis methods in Smart Environments and Prospects

The intelligent Universally Interacting IoT Objects (UIO) ecosystem is deployed at the perception layer in smart systems. Furthermore, application of IoT devices in virtually all domains has outfitted the path for implementing efficient and sustainable intelligent systems. The digital wave heralded the IoT as the globe’s most technical revolution. Cyber-physical systems, Smart ecosystems, digital technologies, and organizations constantly redesign and accept IoT devices. However, the advent of IoT devices has incubated cyber security issues. Researchers have invested efforts in understanding IoT-traffic behavior to defend against such attacks. This paper outlines the attributes of IoT traffic, performs a comparative analysis of existing traffic classification solutions, and recommends future cyber defense solutions based on IoT-traffic characteristics in Smart Environments. The paper also discusses the characteristics of a resilient classification and defense framework. It emphasizes the vital performance metrics and proposes a distributed, resilient, and scalable framework based on intelligent learning approaches.