基于量子遗传算法的入侵检测器生成

Generation of intrusion detection based on quantum genetic algorithm

入侵检测器的生成是入侵检测系统的核心,入侵检测器生成可以转化成数据的最优分类问题.量子遗传算法针对复杂优化问题有很强的搜索能力和最优化性能.因此,本文引入量子遗传算法来实现这个优化过程,并进行了入侵检测对比实验,实验结果表明基于本文算法的检测准确率高,同时收敛稳定性明显提高,收敛速度更快.

The generation of intrusion detection device is the core of the intrusion detection system, and the generation of intrusion detection device can be transformed into the problem of optimal classification of data. In place of complex problem of optimization, quantum genetic algorithm has strong searching capabilities and the most optimal performance. Therefore, this article introduced quantum genetic algorithm to achieve this optimization process, and conducted comparative experiments of intrusion detection. Experimental results showed the high accuracy of the algorithm based on the algorithm of text, markedly improved the stability of convergence, and faster convergence.