References

• 1. 1)
     • 2. Arvidsson, N.: ‘Consumer attitudes on mobile payment services–results from a proof of concept test’, Int. J. Bank Market., 2014, 32, (2), pp. 5–5 (doi: 10.1108/IJBM-05-2013-0048).
  2. 2)
     • 3. Chao, H.-C., Lai, C.-F., Chen, S.-Y., Huang, Y.-M.: ‘A M-learning content recommendation service by exploiting mobile social interactions’, IEEE Trans. Learn. Technol., 2014, 7, (3), pp. 221–230 (doi: 10.1109/TLT.2014.2323053).
  3. 3)
     • 7. Patcha, A., Park, J.M.: ‘An overview of anomaly detection techniques: existing solutions and latest technological trends’, Elsevier Comput. Netw., 2007, 51, (12), pp. 3448–3470 (doi: 10.1016/j.comnet.2007.02.001).
  4. 4)
     • 13. Elman, J.L.: ‘Finding structure in time’, Cognit. Sci., 1990, 14, (2), pp. 179–211 (doi: 10.1207/s15516709cog1402_1).
  5. 5)
     • 4. Chu, H.-C., Lo, C.-H., Chao, H.-C.: ‘The disclosure of an android smartphone's digital footprint respecting the instant messaging utilizing Skype and MSN’, Electron. Commerce Res. J., 2013, 13, (3), pp. 399–410 (doi: 10.1007/s10660-013-9116-1).
  6. 6)
     • 1. Yao, D., Yin, M., Luo, J., et al: ‘Network anomaly detection using random forests and entropy of traffic features’. 2012 Fourth Int. Conf. on Multimedia Information Networking and Security (MINES) IEEE, 2012, pp. 926–929.
  7. 7)
     • 2. Arvidsson, N.: ‘Consumer attitudes on mobile payment services–results from a proof of concept test’, Int. J. Bank Market., 2014, 32, (2), pp. 5–5 (doi: 10.1108/IJBM-05-2013-0048).
  8. 8)
     • 17. Shyu, M.L., Chen, S.C., Sarinnapakorn, K., et al: ‘A novel anomaly detection scheme based on principal component classifier’. In: Proc. of the IEEE Foundations and New Directions of Data Mining Workshop, Melbourne, FL, USA, 2003.
  9. 9)
     • 5. Chen, X., Lian, S.: ‘Secure peer-to-peer multimedia service in E-commerce environments’, J. Internet Technol., 2010, 11, (5), pp. 633–641, see also p. 649.
  10. 10)
      • 18. Nychis, G., Sekar, V., Andersen, D.: ‘Empirical evaluation of entropy-based traffic anomaly detection’. Proc. IMC'08, 2008.
  11. 11)
      • 8. Smaha, S.E.: ‘Haystack: an intrusion detection system’. Fourth IEEE Aerospace Computer Security Applications Conf., 1988, pp. 37–44.
  12. 12)
      • 16. Zhang, Y., Lee, W.: ‘Intrusion detection in wireless ad-hoc networks’. Proc. Sixth Annual Int. Conf. on Mobile Computing and Networking, ACM, 2000, pp. 275–283.
  13. 13)
      • 19. Wagner, A., Plattner, B.: ‘Entropy based worm and anomaly detection in fast IP networks’. Fourteenth IEEE Int. Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprise, 2005, pp. 172–177.
  14. 14)
      • 9. Anderson, D., Frivold, T., Valdes, A.: ‘Next-generation intrusion detection expert system (NIDES): a summary’ (SRI International, Computer Science Laboratory, 1995).
  15. 15)
      • 4. Chu, H.-C., Lo, C.-H., Chao, H.-C.: ‘The disclosure of an android smartphone's digital footprint respecting the instant messaging utilizing Skype and MSN’, Electron. Commerce Res. J., 2013, 13, (3), pp. 399–410 (doi: 10.1007/s10660-013-9116-1).
  16. 16)
      • 14. Niu, X., Xianyi, Y., Wu, Z.: ‘Information hiding theory and key technology research’, Telecommun. Sci., 2004, (12), pp. 28–29.
  17. 17)
      • 15. Chandola, V.: ‘MINDS: Architecture & Design Varun Chandola, Eric Eilertson, Levent Ertoz, Gyorgy Simon, and Vipin Kumar[J]’. 2006.
  18. 18)
      • 10. Lee, W., Xiang, D.: ‘Information-theoretic measures for anomaly detection’. IEEE Symp. on Security and Privacy, 2001 (S&P 2001) IEEE Proc., 2001, pp. 130–143.
  19. 19)
      • 11. Lakhina, A., Papagiannaki, K., Crovella, M., et al: ‘Structural analysis of network traffic flows’. ACM, 2004.
  20. 20)
      • 13. Elman, J.L.: ‘Finding structure in time’, Cognit. Sci., 1990, 14, (2), pp. 179–211 (doi: 10.1207/s15516709cog1402_1).
  21. 21)
      • 3. Chao, H.-C., Lai, C.-F., Chen, S.-Y., Huang, Y.-M.: ‘A M-learning content recommendation service by exploiting mobile social interactions’, IEEE Trans. Learn. Technol., 2014, 7, (3), pp. 221–230 (doi: 10.1109/TLT.2014.2323053).
  22. 22)
      • 12. Amin, M.M., Salleh, M., Ibrahim, S., et al: ‘Information hiding using steganography’. Fourth National Conf. on Telecommunication Technology Proceedings, Shah Alam, Malaysia, 14–15 January 2003.
  23. 23)
      • 6. Liu, C., Xiao, W., Li, J., Xiong, N., Qu, Y.: ‘Modeling of credit option replenishment in cluster supply chain networks under internet environment’, J. Internet Technol., 2013, 14, (4), pp. 561–572, see also p. 577.
  24. 24)
      • 20. Tavallaee, M., Bagheri, E., Lu, W., et al: ‘A detailed analysis of the KDD CUP 99 data set’. Proc. Second IEEE Symp. Computational Intelligence for Security and Defence Applications, 2009.
  25. 25)
      • [24]. Patcha, A., Park, J.M.: ‘An overview of anomaly detection techniques: Existing solutions and latest technological trends’, Comput. Netw., 2007, 51, pp. 3448–3470 (doi: 10.1016/j.comnet.2007.02.001).