An Intelligent Deep Learning Network based on Internet of Things (IoTs): An Enhanced Approach for Network Threat Mitigations, Techniques, Issues and Opportunities

https://doi.org/10.5281/zenodo.18060491

Abstract

Internet of Things (IoT) is among the most commonly utilized technologies nowadays, and it has a substantial impact on our lives in many different ways, including social, commercial, and economical ways. Regarding automation, productivity, as well as the comfort of consumers in diverse application segments, including education and smart cities, the current and future IoT technologies promise significant advancement in the overall human life quality. Nevertheless, cyber-attacks and threats have a significant impact on smart applications in the context of the IoT. The conventional IoT security approaches would not suffice considering the current security issues in the light of the advanced burgeoning of various forms of attacks and threats. The solution to providing an updated and dynamic security system to the next-generation IoT system is to deploy the artificial intelligence (AI) expertise and, specifically, machine, and deep learning solutions. In the entire article, we show a comprehensive image on the IoT security intelligence that is constructed on machine and deep learning technologies that can extract insights of raw data in order to intelligently defend against numerous cyber-attacks on the Internet of Things. Lastly, in line with our research, we bring out the research issues and future directions based on our researches. On the whole, the article aims to become a reference point and guide, especially on the technical level, to cybersecurity experts and researchers operating in the field of IoT.