摘要
为了提高网络大数据轻量级入侵检测能力,提出基于布谷鸟搜索算法的网络大数据轻量级入侵检测方法.首先构建三层网络体系结构,进行网络入侵的体系结构分析,采用布谷鸟寻优方法,在连续空间内搜索最优解,得到网络大数据轻量级入侵调度集函数,分析网络大数据随机序列的分布情况,在此基础上使用一个四元组结构来描述网络大数据轻量级入侵的关联特征,并提取其关键信息,结合布谷鸟搜索算法进行网络大数据轻量级入侵检测过程中的自适应寻优,以实现网络大数据轻量级入侵检测优化.仿真结果表明,采用该方法进行网络大数据轻量级入侵检测的准确性较高,检测过程的收敛性较好.
In order to improve the lightweight intrusion detection ability of network big data,a network big data lightweight intrusion detection method based on cuckoo search algorithm is proposed.A three-tier network archi⁃tecture was constructed.The architecture of network intrusion was analyzed.The cuckoo optimization method was used to search the optimal solution in continuous space.The lightweight intrusion scheduling set function of net⁃work big data was obtained,and the distribution of network big data random sequence was analyzed.On this ba⁃sis,a quaternion structure was used to describe the correlation characteristics of big data lightweight intrusion,and its key information was extracted.In the process of network big data lightweight intrusion detection com⁃bined with cuckoo search algorithm adaptive optimization,network big data lightweight intrusion detection opti⁃mization was achieved.The simulation results show that the method has high accuracy and good convergence in network big data lightweight intrusion detection.
作者
钟元权
ZHONG Yuan-quan(School of Computer Engineering,Anhui Wonder University of Information Engineering,Hefei 231201,China)
出处
《内蒙古民族大学学报（自然科学版）》
2020年第4期286-291,共6页
Journal of Inner Mongolia Minzu University：Natural Sciences
基金
2018安徽省质量工程研究项目(2018jyxm1317)
安徽文达信息工程学院自然研究项目(XZR2018A06)。
关键词
布谷鸟搜索算法
网络
大数据
轻量级
入侵检测
Cuckoo search algorithm
Network
Big data
Lightweight
Intrusion detection
