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《Ship Science and Technology》 2019-06
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Research on real-time detection of hybrid vulnerabilities in ship network information encryption

ZHAO Man-xu;School of Mathematics and Information Technology, Yuncheng University;  
Because the traditional method neglects the evaluation of vulnerability location, the detected vulnerabilities are not comprehensive, and the accuracy of vulnerability location is low, so it can not achieve the desired vulnerability detection effect. Therefore, this paper proposes and designs a hybrid real-time vulnerability detection method based on particle swarm optimization. On the basis of analyzing the characteristics of mixed vulnerabilities, detection rules are established, and real-time detection algorithm is established based on particle swarm optimization theory. The precise vulnerability location can be found by using the information exchange between particle swarm optimization to realize real-time detection and location of mixed vulnerabilities in ship network information encryption. The simulation results show that the detection method based on particle swarm optimization can effectively improve the accuracy of vulnerability detection and vulnerability location, and has very high effectiveness.
【Fund】: 山西省教育科学“十三五”规划课题资助项目(GH-16084);山西省教育科学“十三五”规划课题资助项目(GH-18079);; 山西省高等学校教学改革创新资助项目(J2018170);; 运城学院教改资助项目(JG201733)
【CateGory Index】: U665.2
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