DocumentCode :
2915749
Title :
DDoS intrusion detection using Generalized Grey Self-organizing Maps
Author :
Li, Ding ; Gui-qiang, Ni ; Zhi-Song, Pan ; Gu-Yu, Hu
Author_Institution :
PLA Univ. of Sci. & Technol., Nanjing
fYear :
2007
fDate :
18-20 Nov. 2007
Firstpage :
1548
Lastpage :
1551
Abstract :
This paper describes the application of G2SOM (generalized grey self-organizing maps) to the DDoS(denial of service) intrusion detection. Generalized grey relational coefficients (G2RC), which characterize and stresses the whole correlation relationships between the input pattern and the weights of all the nodes that participate in competition, are explicitly introduced into the learning rule of the traditional SOM. In addition, SOM is generalized by the designed three G2RC functions, namely generalized grey self-organizing maps. Finally, the experiments on the DDOS datasets confirm their validities and feasibilities over the G2SOM in this paper. The dataset used is DARPA/KDD-99 publicly available dataset of features from network packets classified into normal and four DDoS attack categories.
Keywords :
grey systems; learning (artificial intelligence); security of data; self-organising feature maps; DDoS intrusion detection; G2RC; G2SOM; denial of service; generalized grey relational coefficient; generalized grey self-organizing maps; learning rule; Artificial neural networks; Computer crime; Computer networks; Information security; Intelligent systems; Intrusion detection; Neural networks; Self organizing feature maps; Stress; Telecommunication traffic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-1294-5
Electronic_ISBN :
978-1-4244-1294-5
Type :
conf
DOI :
10.1109/GSIS.2007.4443532
Filename :
4443532
Link To Document :
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