Anomaly Bandwidth Usage Detection in LAN Islamic University of Riau using Wireshark Analyzer

  • Authors

    • Sri Listia Rosa Universitas Islam Riau
    • Evizal Abdul Kadir Universitas Islam Riau
    2018-07-14
    https://doi.org/10.14419/ijet.v7i4.17391
  • Internet usage, Detection, LAN, UIR.
  • Increasing internet network traffic in a Local Area Network (LAN) will impact to internet access performance. Abnormal internet traffic monitoring system is very important to detect anomaly usage of internet bandwidth. In Islamic University of Riau (UIR) one of the issue related internet usage and normal method is by tapping a monitoring computer to the main terminal of LAN or source of internet provider. This research proposes a new method of monitoring system that gives detail information by using traffic behavior method and history of traffic connected, whereas detail information of internet bandwidth used is monitored for analysis. In this research case location is in Islamic University if Riau, Indonesia campus LAN area. Results shows graph of monitoring in day time because of student activities only in that time, various website and link access by students and staff in the campus be able to captured including duration with specific time. This method gives continues and accurate data to capture anomaly data use including Internet Protocol (IP) address of computer or device connected. The system help operator to give report related to internet usage and user who connected as well as data used in automatic system.

     

  • References

    1. [1] W. Xiuying, X. Lizhong, and S. Zhiqing, "A Danger-Theory-Based Abnormal Traffic Detection Model in Local Network," in 2008 International Conference on Computer Science and Software Engineering, 2008, vol. 3, pp. 943-946. https://doi.org/10.1109/CSSE.2008.913.

      [2] T. S. Choi et al., "On the design and performance of an Internet application traffic monitoring system," in 2004 IEEE International Workshop on IP Operations and Management, 2004, pp. 41-47.

      [3] M. Alkasassbeh, "A Novel Hybrid Method for Network Anomaly Detection Based on Traffic Prediction and Change Point Detection," Journal of Computer Science, vol. 14, no. 2, 2018. Cornell University Library https://doi.org/10.3844/jcssp.2018.153.162.

      [4] M. Y. Su and S. C. Yeh, "An online response system for anomaly traffic by incremental mining with genetic optimization," Journal of Communications and Networks, vol. 12, no. 4, pp. 375-381, 2010. https://doi.org/10.1109/JCN.2010.6388474.

      [5] B. Siregar, M. S. Manik, R. Rahmat, U. Andayani, and F. Fahmi, "Implementation of network monitoring and packets capturing using random early detection (RED) method," in 2017 IEEE International Conference on Communication, Networks and Satellite (Comnetsat), 2017, pp. 42-47. https://doi.org/10.1109/COMNETSAT.2017.8263571.

      [6] E. A. Kadir, A. Siswanto, and A. Syukur, "Performance analysis of wireless LAN 802.11n standard for e-Learning," in 2016 4th International Conference on Information and Communication Technology (ICoICT), 2016, pp. 1-6. https://doi.org/10.1109/ICoICT.2016.7571948.

      [7] M. J. Vargas-Muñoz, R. Martínez-Peláez, P. Velarde-Alvarado, E. Moreno-García, D. L. Torres-Roman, and J. J. Ceballos-Mejía, "Classification of network anomalies in flow level network traffic using Bayesian networks," in 2018 International Conference on Electronics, Communications and Computers (CONIELECOMP), 2018, pp. 238-243. https://doi.org/10.1109/CONIELECOMP.2018.8327205.

      [8] J. B.MUTHUKUMARb, "Intrusion Detection System (IDS): Anomaly Detection using Outlier Detection Approach," in International Conference on Intelligent Computing, Communication & Convergence (ICCC-2015), 2015, vol. 48: Procedia Computer Science. https://doi.org/10.1016/j.procs.2015.04.191.

      [9] H. Son and Y. Lee, "Detecting Anomaly Traffic using Flow Data in the real VoIP network," in 2010 10th IEEE/IPSJ International Symposium on Applications and the Internet, 2010, pp. 253-256. https://doi.org/10.1109/SAINT.2010.108.

      [10] B. Zhou et al., "Online Internet traffic monitoring system using spark streaming," Big Data Mining and Analytics, vol. 1, no. 1, pp. 47-56, 2018. https://doi.org/10.26599/BDMA.2018.9020005.

      [11] J. Han and J. Z. Zhang, "Network traffic anomaly detection using weighted self-similarity based on EMD," in 2013 Proceedings of IEEE Southeastcon, 2013, pp. 1-5. https://doi.org/10.1109/SECON.2013.6567395.

      [12] Y. Liu, J. Sun, R. Sun, and Y. Wen, "Next Generation Internet Traffic Monitoring System Based on NetFlow," in 2010 International Conference on Intelligent System Design and Engineering Application, 2010, vol. 1, pp. 1006-1009. https://doi.org/10.1109/ISDEA.2010.337.

      [13] S. Ruoning and L. Fang, "Real-time anomaly traffic monitoring based on dynamic k-NN cumulative-distance abnormal detection algorithm," in 2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems, 2014, pp. 187-192. https://doi.org/10.1109/CCIS.2014.7175727.

      [14] N. Bansal and R. Kaushal, "Unusual internet traffic detection at network edge," in 2015 International Conference on Computing and Network Communications (CoCoNet), 2015, pp. 179-185. https://doi.org/10.1109/CoCoNet.2015.7411184.

      [15] M. M. Ahmed, S. Banu, and B. Paul, "Real-time air quality monitoring system for Bangladesh's perspective based on Internet of Things," in 2017 3rd International Conference on Electrical Information and Communication Technology (EICT), 2017, pp. 1-5. https://doi.org/10.1109/EICT.2017.8275161.

      [16] Evizal, T. A. Rahman, and S. K. A. A. Rahim, "Active RFID Technology for Asset Tracking and Management System," TELKOMNIKA, vol. 11, no. 1, pp. 137-146, 2013. https://doi.org/10.12928/telkomnika.v11i1.898.

      [17] S. Lee, S. Shin, and B. Roh, "Abnormal Behavior-Based Detection of Shodan and Censys-Like Scanning," in 2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 2017, pp. 1048-1052. https://doi.org/10.1109/ICUFN.2017.7993960.

      [18] V. Prashanthi, D. S. Babu, and C. V. G. Rao, "Network Coding Aware Routing for Efficient Coomunication in Mobile Ad-Hoc Networks," International Journal of Engineering & Technology, vol. 7, no. 3, pp. 1474-1481, 2018. https://doi.org/10.14419/ijet.v7i3.12928.

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    Listia Rosa, S., & Abdul Kadir, E. (2018). Anomaly Bandwidth Usage Detection in LAN Islamic University of Riau using Wireshark Analyzer. International Journal of Engineering & Technology, 7(4), 6722-6726. https://doi.org/10.14419/ijet.v7i4.17391