Application of EHO Optimization Algorithm in Network Security Detection
With the rapid growth of network resources and the number of users,network security problems have become more complex and difficult to solve.To cope with these problems,this study proposes an improved elephant swarm optimization algorithm and constructs a new intrusion detection model.The experimental results show that the model achieves the maximum fitness value on the data of four attack types,which is significantly better than other algorithms.Compared with the algorithm be-fore the improvement,the improved method improves the correct detection rate of intrusion attack types by 3.65％,7.56％,9.42％,10.13％,and 2.96％ on average,while reducing the average false alarm rate by 5.75％,8.43％,10.03％,3.82％,and 5.01％.In summary,the improved method demon-strates excellent performance and generalization capability in the field of intrusion detection.
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维普
