基于大数据的复杂网络入侵数据智能化检测系统设计  

Design of Intelligent Detection System for Complex Network Intrusion Data Based on Big Data

作　　者：赵卫 方诚 ZHAO Wei;FANG Cheng(Information Technology Office,Xianyang Normal University,Xianyang 712000 China)

机构地区：[1]咸阳师范学院信息化建设办公室,陕西咸阳712000

出　　处：《自动化技术与应用》2021年第11期164-167,共4页Techniques of Automation and Applications

摘　　要：随着网络复杂度增加,目前的安全技术无法检测到复杂网络的攻击,因此数据安全正面临着严峻的挑战。以前的网络攻击以简单的黑客攻击和破坏系统动机为主,而如今,已从攻击系统或网络变为大规模数据攻击。当前针对网络攻击的安全技术以模式匹配方法为主,而这种方法非常有限。因此,在面对新的和未知的攻击的情况下,检测率变得非常低。因此,设计了一套复杂网络入侵数据智能化检测系统,该系统基于大数据的新模型来检测未知攻击,结果证明该系统可作为未来高级持久威胁(APT)检测和预防系统实施的基础。As network complexity increases,current security technologies cannot detect attacks on complex networks,so data security is facing severe challenges.In the past,network attacks are mainly based on simple hacking and system destruction,but now they change from attacking systems or networks to large-scale data attacks.The current security technology for network attacks is mainly based on pattern matching methods,and this method is very limited.Therefore,in the face of new and unknown attacks,the detection rate becomes very low.Therefore,an intelligent detection system for complex network intrusion data is designed.This system detects unknown attacks based on a new model of big data.The results prove that the system can be used as the basis for the implementation of future advanced persistent threat(APT)detection and prevention systems.

关 键 词：复杂网络 数据安全 模式匹配法 智能化检测 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]