Title :
Research of intrusion detection system based on neural networks
Author :
Zhao, Jinguo ; Chen, Min ; Luo, Qinyun
Author_Institution :
Dept. of Comput. Sci. & Technol., Hunan Inst. of Technol., Hengyang, China
Abstract :
Through in-depth study on the existing technologies about intrusion detection system, to accelerate the detection speed and improve the accuracy, this paper presents a new intrusion detection model based on neural networks. This model uses neural networks to detect, transforms the pattern recognition into numerical calculation, thereby speeding up the detection rate, while combining with expert system detection and real-time neural network training set to improve the detection accuracy.
Keywords :
expert systems; neural nets; pattern recognition; security of data; detection accuracy; detection rate; detection speed; expert system detection; intrusion detection system; numerical calculation; pattern recognition; real-time neural network training set; Biological neural networks; Computational modeling; Databases; Intrusion detection; Training; intrusion detection; network security; neural network;
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
DOI :
10.1109/ICCSN.2011.6013688
