量子驱动的克隆选择在入侵检测中的应用

将量子计算技术与克隆选择算法结合，通过对量子编码的检测器进行测量来生成二进制检测器（测量解）在得到的多个测量解中只保存亲和力最高的。既提高了种群多样性避免了早熟，又减少了检测器冗余。在变异过程中，通过对父代检测器和子代检测器进行比较来对变异进行指导，使其向着亲和力更高的方向进行。加快了种群的进化速度。仿真实验表明，同传统克隆选择算法相比，该算法避免了种群进化过程出现的早熟和进化速度慢以及检测器冗余的问题，提高了系统的检测率。

Application of quantum-inspired clonal selection in IDS

In this paper,the quantum computing technology and the clonal selection is combined.The binary detector（observed solution） is formed by observing the quantum detector.Only the observed solution which has the biggest avidity is preserved.In this way,the prematurity and the detector redundant is avoided.In the process of mutation,the comparison between the progenitor detector and the progeny detector is made for guiding the mutation.It makes the mutation go forward the direction of higher avidity and,the converging speed is improved.Simulation tests show that compared with the traditional clonal selection algorithm the quantum-inspired clonal selection algorithm avoid the problem of prematurity,low converging speed and detector redundant,improving the efficiency of detector optimization.