DDoS detection method based on chaos analysis of network traffic entropy

IEEE Communications Letters

Volumn 18, Issue 1, 2014, Pages 114-117

  Ma, Xinlei ^a   Chen, Yonghong ^a  

^a HUAQIAO UNIVERSITY   (China)

Author keywords

Anomaly detection; chaotic; entropy; Lyapunov exponent

Indexed keywords

ANOMALY DETECTION; CHAOS ANALYSIS; CHAOTIC; DISTRIBUTED DENIAL OF SERVICE; ENTROPY-BASED METHODS; FLOODING ATTACKS; LYAPUNOV EXPONENT; NETWORK TRAFFIC;

DIFFERENTIAL EQUATIONS; LYAPUNOV FUNCTIONS; LYAPUNOV METHODS; NETWORK SECURITY;

ENTROPY;

EID: 84893749338     PISSN: 10897798     EISSN: None     Source Type: Journal    
DOI: 10.1109/LCOMM.2013.112613.132275     Document Type: Article

References (13)

1. J. Mirkovic and P. Reiher, A taxonomy of DDoS attack and DDoS denfense mechanisms, ACM SIGCOMM Computer Commun. Rev., vol. 34, no. 2, pp. 39-53, 2004.
2. A. Lakhina, M. Crovella, and C. Diot, Mining anomalies using traffic feature distributions, in Proc. 2005 Conference on Applications, Technologie, Architectures and Protocols for Computer Communications, pp. 217-228.
3. A. Ziviani, A. Gomes, M. Monsores, and P. Rodrigues, Network anomaly detection using nonextensive entropy, IEEE Commun. Lett., vol. 11, no. 12, pp. 1034-1036, 2007.
4. H. Rahmani, N. Sahli, and F. Kamoun, DDoS flooding attack detection scheme based on F-divergence, Computer Commun., vol. 35, no. 11, pp. 1380-1391, 2012.
5. A. Chonka, J. Singh, and W. Zhou, Chaos theory based detection against network mimicking DDoS attacks, IEEE Commun. Lett., vol. 13, no. 9, pp. 717-719, 2009.
6. G. Carl, G. Kesidis, R. R. Brooks, R. Richard, and S. Rai, Denial-ofservice attack-detection techniques, Internet Computeing, vol. 10, no. 1, pp. 82-89, 2006.
7. S. Yu, W. Zhou, R. Doss, and W. Jia, Traceback of DDoS attacks using entropy variations, IEEE Trans. Parallel Distrib. Syst., vol. 22, no. 3, pp. 412-425, Mar. 2011.
8. Y. Xiang, K. Li, and W. Zhou, Low-rate DDoS attacks detection and traceback by using new information metrics, IEEE Trans. Inf. Forensics and Security, vol. 6, no. 2, pp. 426-437, June 2011.
9. Y Chen, X. Ma, and X. Wu, DDoS detection algorithm based on preprocessing network traffic predicted method and chaos theory, IEEE Commun. Lett., vol. 17, no. 5, pp. 1052-1054, 2013.
10. C. Tsallis, Possible generalization of Boltzmann-Gibbs statistics, J. Statistical Physics, vol. 52, no. 1-2, pp. 479-487, 1988.
11. X. Zeng, R. Eykholt, and R. A. Pielke, Estimating the Lyapunovexponent spectrum from short time series of low precision, Physical Rev. Lett., vol. 66, no. 25, pp. 3229-3232, 1991.
12. J. McHugh, The 1998 Lincoln Laboratory IDS evaluation, in Recent Advances in Intrusion Deteciton. Springer, 2000, pp. 145-161.
13. MIT Lincoln Lab (DDoS 1.0). Available: http://www.ll.mit.edu/IST/ideval/ data/2000/LLSDDOS1.0.html