make the fuzzy clustering Linux system anomaly intrusion detection mode
through the network information classification the dynamic test
can reduce the intrusion detection miss rate
dynamic to detect the network data flow under the condition of the invasion of the larger program
avoid the traditional way of intrusion detection.It is proved by experiment based on fuzzy clustering of intrusion detection means to be able to quickly and accurately
to detect the invasion and procedures to ensure the Linux system system security.
A traffic anomaly detection model integrating class-selective encoder and CTGAN
An improved intrusion detection method for GraphSAGE
Improved grey wolf optimization algorithm for intrusion detection feature selection
Based ontwice decision for deep learning intrusion detection model
A Fast-Fractal Image Coding Based on Complex Exponent Moments and Fuzzy Clustering
Related Author
YANG Zi
WU Cong
JIN Haibo
WANG Jinwei
CHEN Hong
LIU Shifeng
SHEN Xueli
鲍杰
Related Institution
College of Innovation Practice, Liaoning University of Engineering Technology
College of Software, Liaoning University of Engineering Technology
College of Software, Liaoning Technical University
广西民族大学 机构 电子信息学院
Guilin University of Electronic Technology Guangxi Key Laboratory of Imageand Graphic Intelligent Processing, Guilin University of Electronic Technology