A Novel Framework for Early Intelligent Vulnerability Detection Algorithm for IoT Technology Environments

Abstract

This paper specifically studies the vulnerability intelligent early warning technology withinside the IoT environment, and studies the network protection assessment method based totally definitely on the attack graph affiliation assessment of the IoT environment, and analyzes the attack graph era set of policies. Firstly, it uses the attack graph technology to installation a network protection evaluation model based totally definitely on the vulnerability affiliation assessment withinside the IoT environment. The attack graph generation algorithm policies are improved. The key attack path of the attack graph withinside the IoT environment is searched constant with the node weight value. The key attack path of the network attack graph is used to diploma the complete network protection, and the protection of the IoT environment is given. The length calculation model is used to recognize the quantitative assessment of the protection recognition of the IoT environment thru manner of way of using the attack graph. Secondly, an intelligent early warning vulnerability detection algorithm based on the dynamic stain propagation model in the IoT environment is proposed, focusing on the introduction of stains and the inspection of stains. A static detection method for early warning vulnerabilities based on the counter-example of the IoT is proposed. Through the ow detection and context sensitive detection, a possible buffer early warning vulnerability is discovered. The driver crawler realizes automatic detection, and uses function hijacking to detect the execution of the stain data. In the experimental environment, compared with the existing tools, the experimental data shows that the algorithm improves the accuracy, recall rate and efficiency of the unfiltered vulnerability of intelligent early warning detection, and proves that the proposed algorithm can effectively detect the vulnerability.