基于计算智能的网络安全智能课程学习

Irawan Dwi Wahyono, Khoirudin Asfani, Mohd Murtadha Mohamad, Djoko Saryono, H. Putranto, W. Wibisono
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引用次数: 0

摘要

本研究开发了一门学习网络安全的智能课程。该智能课程使用计算智能(CI)对网络安全学习模块中的用户能力进行分类。在这门智能课程中,使用其他计算智能来为学生提供网络安全模块的建议,学生可以根据先前获得的能力进行工作。本研究使用的算法计算智能是k-最近邻和贝叶斯网络(BN)。基于智能课程中每个模块的预测试,k-NN算法对用户的能力进行分类。利用贝叶斯网络算法,根据用户的意愿和能力为用户提供进一步的模块。在这个智能课程上,k-NN和贝叶斯网络的测试结果平均准确率为85%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Courses Learning for Network Security using Computational Intelligence
This research develops a smart course to study network security. This smart courser uses computational intelligence (CI) to classify the user's capabilities in the network security learning module. The use of other computational intelligence is used in this smart course to provide suggestions on network security modules that students can work on based on previously acquired abilities. The algorithm computational intelligence used in this study is k-Nearest Neighbor and Bayesian Network (BN). The k-NN algorithm to classify the user's capabilities based on the pre-test of each module on the smart course. The Bayesian Network algorithm is used to provide further modules to the user by the wishes and abilities of the user. The k-NN and Bayesian Network test results on this smart course have an average accuracy of 85%.
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