Research on the Optimization Scheme of Intelligent Algorithms in the Improvement of Cyber Attack and Defense Ability of Students in Applied Colleges and Universities

Abstract

Enhancing students' cyber defense capabilities is a crucial measure to help them maintain their ability to identify threats and protect their legitimate rights and interests. In light of this, this study integrates and analyzes the influencing factors of cyber defense capability cultivation among students in applied universities, employs the entropy weight method to rank and combine these factors based on their importance, and optimizes the optimal combination tailored to students' individual circumstances. A two-level fuzzy comprehensive evaluation system is established to assess students' cyber defense capabilities. An improved particle swarm optimization algorithm is employed to solve the optimization model, followed by numerical simulation experiments. Experimental results indicate that compared to other improved multi-objective algorithms, the proposed algorithm demonstrates excellent convergence and diversity, and effectively achieves the enhancement of cyber defense capabilities based on this algorithm. Based on the actual assessment and feedback of this method from a certain applied university, measures to enhance network defense capabilities are proposed, namely, ensuring the effectiveness of network security ideological and political management through institutional safeguards, publicity and education, technical support, security management assessments, and the cultivation of high-quality management teams.