N. Hoque, M. H. Bhuyan, R. C. Baishya, D. K. Bhattacharyya, and J. K. Kalita, Network attacks: Taxonomy, tools and systems, Journal of Network and Computer Applications, vol.40, pp.307-324, 2014.
DOI : 10.1016/j.jnca.2013.08.001

A. Networks, S. Ddos, and . Feed, Retrieved 20-03- 2014 from http, p.2014

D. Wang and . Zhu, A multi-core based DDoS detection method, 3rd IEEE International Conference on, pp.115-124, 2010.

G. Loukas and G. Oke, Protection Against Denial of Service Attacks: A Survey, The Computer Journal, vol.53, issue.7, p.10201037, 2010.
DOI : 10.1093/comjnl/bxp078

J. Mirkovic and P. Reiher, A taxonomy of DDoS attack and DDoS defense mechanisms, ACM SIGCOMM Computer Communication Review, vol.34, issue.2, pp.39-53, 2004.
DOI : 10.1145/997150.997156

J. Mirkovic and D. , DDoS network attack recognition and defense, PhD dissera-tion prospectus, 2002.

T. Thapngam, S. Yu, W. Zhou, and S. K. Makki, Distributed Denial of Service (DDoS) detection by traffic pattern analysis. Peer-to-Peer Networking and Applications, pp.1-13, 2012.

M. Kim, A combined data mining approach for DDoS attack detection Infor-mation Networking. Networking Technologies for Broadband and Mobile Networks, pp.943-950, 2004.

G. Oke and G. Loukas, A Denial of Service Detector based on Maximum Likeli-hood Detection and the Random Neural Network. The Computer Journal, pp.717-727, 2007.

H. Rahmani, N. Sahli, and F. Kamoun, DDoS flooding attack detection scheme based on F-divergence, Computer Communications, vol.35, issue.11, pp.1380-1391, 2012.
DOI : 10.1016/j.comcom.2012.04.002

J. Yu, H. Kang, D. Park, H. Bang, and D. W. Kang, An in-depth analysis on traffic flooding attacks detection and system using data mining techniques, Journal of Systems Architecture, vol.59, issue.10, pp.1005-1012, 2013.
DOI : 10.1016/j.sysarc.2013.08.008

K. Hwang, M. Cai, and Y. Chen, Hybrid Intrusion Detection with Weighted Signature Generation over Anomalous Internet Episodes, Dependable and Secure Compu-ting, IEEE Transactions on, vol.4, issue.1, pp.41-55, 2007.

F. Wang, H. Wang, X. Wang, and J. Su, A new multistage approach to detect subtle DDoS attacks, Mathematical and Computer Modelling, vol.55, issue.1-2, pp.198-213, 2012.
DOI : 10.1016/j.mcm.2011.02.025

G. Oke, G. Loukas, and E. Gelenbe, Detecting denial of service attacks with bayesian clas-sifiers and the random neural network, Fuzzy Systems Conference, pp.1-6, 2007.

K. Xylogiannopoulos, P. Karampelas, and R. Alhajj, Periodicity data mining in time series using Suffix Arrays, 2012 6th IEEE INTERNATIONAL CONFERENCE INTELLIGENT SYSTEMS, 2012.
DOI : 10.1109/IS.2012.6335132

K. Xylogiannopoulos, P. Karampelas, and R. Alhajj, Exhaustive Patterns Detection In Time Se-ries Using Suffix Arrays, p.2012

K. Xylogiannopoulos, P. Karampelas, and R. Alhajj, Minimization of Suffix Arrays Storage Capacity for Periodicity Detection in Time Series, Proc. IEEE International Conference in Tools with Artificial Intelligence, 2012.

K. Xylogiannopoulos, P. Karampelas, and R. Alhajj, Experimental Analysis on the Normality of pi, e, phi and square root of 2 Using Advanced Data Mining Techniques, Experimental Mathematics, 2014.

K. Xylogiannopoulos, P. Karampelas, and R. Alhajj, Analyzing Very Large Time Series Using Suffix Arrays, Applied Intelligence, submitted for publication, 2014.

U. Manber and G. Myers, Suffix Arrays: A New Method for On-Line String Searches, Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms, pp.319-327, 1990.
DOI : 10.1137/0222058