Automated detection of security vulnerabilities in communication networks based on weighted k-neighborhoods
Security vulnerability detection in wireless communication networks is an important task to protect the security of wire-less communication networks.Traditional detection methods suffer from inefficiency and high error rate.Therefore,the study proposes an automated detection method for security vulnerabilities in wireless communication networks based on weighted k-neighborhood.Firstly,network security vulnerabilities are detected using k-neighborhood,and then the concept of weights is introduced to improve the performance of vulnerability detection,and finally,a dataset is used to verify the performance of the constructed method.The re-sults show that under the same vulnerability detection context,the average accuracy of vulnerability detection by weighted k-neighbor-hood is 93.26％,and the detection takes 4.2 s in 200 vulnerability data.This indicates that the constructed detection method is of practical significance for the security protection of wireless communication networks with high accuracy and robustness,which can help to improve the security and reliability of wireless communication networks.
万方数据
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