Advance Identification of Cloning Attacks in Online Social Networks

  • Authors

    • Megha Renuka Prasad
    • Santhosh Kumar B J
    2018-07-15
    https://doi.org/10.14419/ijet.v7i3.10.15636
  • Area of Interest, Clone Attacks, Fake Profiles, Frequent Pattern, Online Social Network,

  • Abstract

    Online social networks (OSN) have changed the way individuals collaborate and convey to reconnect with old companions, acquaintances and set up new associations with others considering leisure activities, interests, and fellowship circles. Shockingly, the member's lamentable acknowledgment of reckless conduct in sharing data, often worthless safety efforts from part of the framework heads and, at last, take advantage of the distributed data in Online Social networks as an intriguing objective to attackers. As OSN is becoming increasingly popular and identity cloning attacks (ICA) mechanism designed to fake the identity of users on OSN is becoming one significant growth concerns. This attack has been seriously affected the victims and other users to establish the relationship of trust, if there is no active application defense.

    In this paper, the first step analyzes the member constraints and characterize the profiles based on their behavior. Then focusing on the categorized profiles of the framework and verify each of them using their area of interests. To detect suspicious identities, two methods are followed based on attribute similarity of profiles and by verifying similar profiles in a cross-site environment by their area of interests.

     

     

  • References

    1. [1] Naruchitparames, J., Güneş, M. H., & Louis, S. J. (2011, June). Friend recommendations in social networks using genetic algorithms and network topology. In Evolutionary Computation (CEC), 2011 IEEE Congress on (pp. 2207-2214). IEEE.

      [2] Sebastiani, F. (2002). Machine learning in automated text categorization. ACM computing surveys (CSUR), 34(1), 1-47.

      [3] Thilagavathi, N., & Taarika, R. (2014, March). Content based filtering in online social network using inference algorithm. In Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on (pp. 1416-1420). IEEE.

      [4] Fortunato, S. (2010). Community detection in graphs. Physics reports, 486(3), 75-174.

      [5] Eslami, M., Aleyasen, A., Moghaddam, R. Z., & Karahalios, K. (2014, November). Friend grouping algorithms for online social networks: preference, bias, and implications. In International Conference on Social Informatics (pp. 34-49). Springer, Cham.

      [6] Labade, S., & Kini, S. N. (2006). A survey paper on frequent item set mining methods and techniques. International Journal of Science and Research. Jia, YW, Wang, H., and Yan, DH, 534-542.

      [7] Devmane, M. A., & Rana, N. K. (2014, May). Detection and prevention of profile cloning in online social networks. In Recent Advances and Innovations in Engineering (ICRAIE), 2014 (pp. 1-5). IEEE.

      [8] Hasan, M. M., Shaon, N. H., Al Marouf, A., Hasan, M. K., Mahmud, H., & Khan, M. M. (2015, December). Friend recommendation framework for social networking sites using user's online behavior. In Computer and Information Technology (ICCIT), 2015 18th International Conference on (pp. 539-543). IEEE.

      [9] Jin, L., Takabi, H., & Joshi, J. B. (2011, February). Towards active detection of identity clone attacks on online social networks. In Proceedings of the first ACM conference on Data and application security and privacy (pp. 27-38). ACM.

      [10] Kontaxis, G., Polakis, I., Ioannidis, S., & Markatos, E. P. (2011, March). Detecting social network profile cloning. In Pervasive Computing and Communications Workshops (PERCOM Workshops), 2011 IEEE International Conference on (pp. 295-300). IEEE.

      [11] Shan, Z., Cao, H., Lv, J., Yan, C., & Liu, A. (2013, January). Enhancing and identifying cloning attacks in online social networks. In Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication (p. 59). ACM.

      [12] Conti, M., Poovendran, R., & Secchiero, M. (2012, August). Fakebook: Detecting fake profiles in on-line social networks. In Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on (pp. 1071-1078). IEEE.

      [13] Matin, A. I., Jahan, S., & Huq, M. R. (2014, December). Community recommendation in social network using strong friends and quasi-clique approach. In Electrical and Computer Engineering (ICECE), 2014 International Conference on (pp. 453-456). IEEE.

      [14] Banerjee, S., & Niyogi, R. (2015, August). A method for community recommendation for social networks. In Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on (pp. 2341-2347). IEEE.

      [15] Brandes, P., & Wattenhofer, R. (2012, October). On finding better friends in social networks. In Symposium on Self-Stabilizing Systems (pp. 266-278). Springer, Berlin, Heidelberg.

      [16] Raju, E., & Sravanthi, K. (2012). Analysis of social networks using the techniques of web mining. International Journal, 2(10).

      [17] Kharaji, M. Y., Rizi, F. S., & Khayyambashi, M. R. (2014). A new approach for finding cloned profiles in online social networks. ArXiv preprint arXiv: 1406.7377.

      [18] Fire, M., Goldschmidt, R., & Elovici, Y. (2014). Online social networks: threats and solutions. IEEE Communications Surveys & Tutorials, 16(4), 2019-2036.

      [19] Kamhoua, G. A., Pissinou, N., Iyengar, S. S., Beltran, J., Kamhoua, C., Hernandez, B. L., ... & Makki, A. P. (2017, June). Preventing Colluding Identity Clone Attacks in Online Social Networks. In Distributed Computing Systems Workshops (ICDCSW), 2017 IEEE 37th International Conference on (pp. 187-192). IEEE.

      [20] Kiruthiga, S., & Kannan, A. (2014, April). Detecting cloning attack in Social Networks using classification and clustering techniques. In Recent Trends in Information Technology (ICRTIT), 2014 International Conference on (pp. 1-6). IEEE.

      [21] Wang, Z., Liao, J., Cao, Q., Qi, H., & Wang, Z. (2015). Friendbook: a semantic-based friend recommendation system for social networks. IEEE transactions on mobile computing, 14(3), 538-551.

      1. Asok, Jisha, T. J., S. Ashok, and Dr. M.V. Judy, “Integrated framework using frequent pattern for clustering numeric and nominal data setsâ€, Advances in Intelligent Systems and Computing, vol. 408, pp. 523-530, 2016.

      [22] M. S. Pallavi, Hegde, V., Anushadevi, H. G., and Ambika, V., “Automated spam detection in e-mail using SVMâ€, International Journal of Applied Engineering Research, vol. 10, pp. 25219-25228, 2015.

  • Downloads

  • How to Cite

    Renuka Prasad, M., & Kumar B J, S. (2018). Advance Identification of Cloning Attacks in Online Social Networks. International Journal of Engineering & Technology, 7(3.10), 83-87. https://doi.org/10.14419/ijet.v7i3.10.15636

    Received date: 2018-07-14

    Accepted date: 2018-07-14

    Published date: 2018-07-15