摘要
随着社会信息化建设的不断发展,互联网成为许多行业的基础平台,DDoS攻击严重威胁到网络的安全.针对DDoS攻击对网络造成的严重威胁问题,提出了利用生物免疫原理来研究DDoS攻击的检测方法,在该方法中,利用信息熵、响应率和参数变化比率等方法进行特征提取,建立DDoS特征库,在此特征库的基础上通过DDoS检测算法实现对DDoS攻击的识别与过滤.实验结果证明该方法可行、有效,为DDoS攻击的检测与防范提供重要依据.
With the continuous development of social informatization construction, Internet has become the basic platform for many industries, DDoS attacks have been a serious threat to network security. For the serious threat, a detection method is proposed to study the DDoS attacks using the biological immune principle. In this method, information entropy, service rate and the rate of change parameters are used to establish the DDoS feature library. On the basis of the library, DDoS detection algorithm is proposed to achieve the recognition and filteration of DDoS attacks. Experimental results show that the method is feasible and efficient, provides an important evidence for DDoS attack prevention and detection.
作者
高大伟
申杰
沈学利
王兆福
Gao Dawei;Shen Jie;Shen Xueli;Wang Zhaofu(Unit 92941 of PLA,Huludao,Liaoning 125000;School of Softuare,Liaoning Technical University,Huludao,Liaoning 125105)
出处
《信息安全研究》
2022年第11期1129-1134,共6页
Journal of Information Security Research
基金
国家自然科学基金面上项目(62173171)。
关键词
生物免疫原理
DDOS攻击
特征提取
DDoS检测算法
信息熵
biological immune principle
DDoS attacks
feature extraction
DDoS detection algorithm
information entropy
