Cyber-attack tasks are expanding due to the increasing use of Internet networks, which are viewed as a “critical” risk to the security of transmitted and received data in the event of a cyber-attack. Cyber-attacks mainly affect a large amount of data, reduce the security of its transmission, and cause denial of service (DoS) and transmission failures. The objectives of cyber-assault location are to distinguish the kind of cyber-assault to give extra concentrated understanding into application originators as well as progressing requests for security. Programmers are working to create a proof system that can identify attacks such as DoS, malware appropriately from the beginning. In this review, hybrid shrewd algorithms were utilized with obtaining guard strategies in view of an artificial intelligence-driven change algorithm. Hybrid strategies have been proposed to precisely recognize vindictive way of behaving of information impacted by the impacts of different cyberattacks. An improved artificial intelligence strategy that upgrades the cautious efficiency of the proposed structure in recognizing cyberattacks is planned and carried out. The proposed thought was executed and tried on a cluster of 2000 samples of the proposed system exhibition, its effect tried, and evaluated utilizing UDP flood attacks rather than existing ventures focused on overseeing DoS attacks with MSE of 0.28%, and regression efficiency of 99%.