Vulnerability Analysis at Industrial Internet of Things Platform on Dark Web Network Using Computational Intelligence

Due to the potentially catastrophic effects in the event of an attack, security-enabled design and algorithms are required to protect automated applications and instruments based on Internet Industries of Thing called as IIoT. The most potential developed techniques for analyzing, designing, and protecting the Internet of Things (IoT) technologies are computational intelligence and big data analysis. These strategies will also help to enhance the protection of IIoT networks (home automation, traffic lighting, power stations, oil and gas stations, smart warehouses, automated vehicles, smart robotics). First, we present the popular IIoT computational intelligence (CIA) algorithm and its related vulnerabilities in this article. We then conduct a cyber-threat-vulnerability review by investigating the use of CIA model to combat illicit behaviors of dark Web environment. The proposed work is based on the literature data analysis within the available solutions for the prevention of cyber terrorism threats using algorithm models of computational intelligence (CIA) is then discussed. Finally, we address our work, which provides scenario of a real-world hidden cyber world activities designed to carry out a cyber terrorist attack and to build a structure for a cyber threat. Device attacks to illustrate how a CIA-based vulnerability analysis system will do well to detect these attacks. To have a rational point of view on the success of the approaches, we have measured the performance across representative metrics.