Yabin Xu, Xiaoqiang Li, and Xiaowei Xu


  1. [1] ONF, Software-defined networking: The new norm for networks, ONF White Paper, 2012.
  2. [2] L. Cui, F.R. Yu, and Q. Yan, When Big Data Meets SoftwareDefined Networking: SDN for Big Data and Big Data for SDN, IEEE Network, 30(1), 2016, 58–65.
  3. [3] X. Li and Y. Xu, SDN access control strategy based on LE-Trie, Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 27(5), 2015, 674–682.
  4. [4] C. Cui and Y. Xu. Research on load balance method in SDN, International Journal of Grid and Distributed Computing, 9(1), 2016, 25–36.
  5. [5] J. Wang, L. Li, and Y. Zheng, Research on mobile search user behavior review based on log mining, Information Studies: Theory & Application, 37(3), 2014, 134–139.
  6. [6] R. Wang and Yi. Yuan, An empirical study of user behavior analysis based on web log mining, Library Tribune, 31(4), 2011, 100–102.
  7. [7] Z. Ling and N. Hua, Research of user’ searching behavior of library new technology of library resource discovery, New Technology of Library and Information Service, 18(12), 2011, 74–78.
  8. [8] H. Song, D. Wei, and G. Tang, Anomaly detection of single user behaviors based on pattern mining, Journal of Chinese Computer Systems, 37(2), 2016, 221–226.
  9. [9] Z. Tao, Abnormal network behavior detection technology based on statistical learning, Big Data Research, 1(4), 2015, 1–10.
  10. [10] W. Jian, Z. Zhizhong, and L. Yunlong, Design and implementation of DPI-based user’s behavior perception system in LTE network, Telecommunications Science, 30(7), 2014, 77–83.
  11. [11] X. Xiao, Q. Zhai, X. Tian, and X. Chen, Novel method for anomaly detection of user behavior based on shell commands and DTMC models, Computer Science, 38(11), 2011, 54–58.
  12. [12] X. Tian, M. Duan, and C. Sun, Detection of anomalous user behavior based on shell commands and hidden Markov models, Journal of Applied Sciences, 26(2), 2008, 175–181.
  13. [13] P. Qiao and M. Li, A research on an improved intranet users’ behavior audit model, Journal of Harbin University of Science and Technology, 16(05), 2011, 57–60.
  14. [14] Y. Xu, The abnormal network traffic recognition method based on optimized BP ANN model, International Journal of Future Generation Communication and Networking, 8(3), 2015, 61– 70.
  15. [15] C. Qiu, Y. Xu, Y. Li, et al., A fast identification approach to social network traffic based on unsupervised learning, Mathematics in Practice and Theory, 44(3), 2014, 100–107.
  16. [16] X. Liu and Y. Xu, Design of peer-to-peer traffic classification system model based on cloud computing, Applied Mechanics and Materials , 182–183, 2012, 1347–1351.
  17. [17] Z. Luo, F. Ding, and X. Jiang, New progress on community detection in complex networks, Journal of National University of Defense Technology, 33(1), 2011, 47–52.
  18. [18] G. Tan, Research on complex network pattern mining algorithm (Xi’an: Xidian University, 2012).
  19. [19] Z. Zhang, Y. Li, J. Wang, et al. User behavior perception based on mining complex network, SCIENCE CHINA Information Sciences, 44(9), 2014, 1069–1083.
  20. [20] J. Wang, J. Wang, H.-Y. Jiao, and Y. Wang, A method of OpenFlow-based real-time conflict detection and resolution for SDN control policies, Chinese Journal of Computers, 38(4), 2015, 873–883.
  21. [21] X.-L. Wang, M. Chen, and C.-Y. Xing, SDSNM: A software defined security networking mechanism to defend against DDoS attacks, Journal of Software, 27(1), 2016, 2–15.
  22. [22] J. Yang and Y. Zhuang, Towards behavior control for evolutionary robot based on RL with ENN, Iaes International Journal of Robotics & Automation, 1(2), 2013, 463–474.
  23. [23] H. Omranpour and S. Shiry, Reduced search space algorithm for simultaneous localization and mapping in mobile robots, IAES International Journal of Robotics & Automation, 1(1), 2012, 49–63.
  24. [24] M.E.J. Newman, Detecting community structure in networks, European Physical Journal B, 38, 2004, 321–330.
  25. [25] M.E.J. Newman, Fast algorithm for detecting community structure in networks, Physical Review E, 69, 2004, 066133.
  26. [26] M. Girvan and M.E.J. Newman, Community structure in social and biological networks, Proceedings of the National Academy of Sciences of the United States of America, 9, 2002, 7821–7826.
  27. [27] A. Clauset, M.E.J. Newman, and C. Moore, Finding community structure in very large networks, Physical Review E, 70, 2004, 066111.
  28. [28] H. Han, J. Wang, and H. Wang, Improving CNM algorithm to detect community structures of weighted network, Computer Engineering and Applications, 46(35), 2010, 86–89.
  29. [29] F. Havemann, M. Heinz, A. Struck, et al., Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels, Journal of Statistical Mechanics Theory & Experiment, 1(01), 2011, 10–23.
  30. [30] F. Ding, Z. Luo, J. Shi, et al., Overlapping community detection by Kernel-based fuzzy affinity propagation, ISA’ 2010, Wuhan, China, 2010.
  31. [31] C. Liu, Y. Xu, and Z. Wu, Method of rapid detecting microblog communities, Journal of Frontiers of Computer Science and Technology, 9(9), 2015, 1100–1107.

Important Links:

Go Back