Abstract
The computer network faces any kind of unauthorized activities i.e. Network Intrusion (NI). The detection of these NI needs a better understanding of how the attacks work. The NI detection is necessary to protect the system information in current activities of the cyber attacks. This paper is intended to improve the security aspect in the Wireless Local Area Network (WLAN) by implementing a machine learning approach i.e. Support Vector Machines (SVMs). In this, the computer lab generated data are used for experimentation. The SVM detects the NI by recognizing the patterns of attack. The simulation outcome of the proposed security framework recognizes the NI and bells the alarm. The analysis of this security system is performed by considering the efficiency of detection and false alarm rate that offers significant coverage and effective detection.
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References
Patel, A., Qassim, Q., Wills, C.: A survey of intrusion detection and prevention systems. Inf. Manag. Comput. Secur. J. 18(4), 277–290 (2010)
Kim, J., Bentley, P.J., Aickelin, U., Greensmith, J., Tedesco, G., Twycross, J.: Immune system approaches to intrusion detection – a review. Nat. Comput. 6(4), 413–466 (2007)
Loo, C.E., et al.: Intrusion detection for routing attacks in sensor networks. Int. J. Distrib. Sens. Netw. 2(4), 313–332 (2006)
Wu, H., Freedman, J., Ivory, C.J.: Network intrusion detection and analysis system and method. US Patent 7,493,659, 17 Feb 2009
Guerrero-Zapata, M., et al.: The future of security in wireless multimedia sensor networks. Telecommun. Syst. 45(1), 77–91 (2010)
Uppuluri, P., Sekar, R.: Experiences with specification-based intrusion detection. In: Lee, W., Wespi, L.M.A. (eds.) Recent Advances in Intrusion Detection, Lecture Notes in Computer Science, vol. 2212, pp. 172–189 (2001)
Sekar, R., Gupta, A., Frullo, J., Shanbhag, T., Tiwari, A., Yang, H., Zhou, S.: Specification-based anomaly detection: a new approach for detecting network intrusions. In: Proceedings of the 9th Conference on Computer and Communications Security, CCS 2002, Washington, DC, USA, pp. 265–274 (2002)
Mitchell, R., Chen, I.R.: Behavior rule based intrusion detection for supporting secure medical cyber physical systems. In: International Conference on Computer Communication Networks, Munich, Germany (2012)
Berthier, R., Sanders, W.: Specification-based intrusion detection for advanced metering infrastructures. In: Proceedings of the 17th Pacific Rim International Symposium on Dependable Computing, Pasadena, CA, USA, pp. 184–193 (2011)
Cárdenas, A.A., Amin, S., Lin, Z.-S., Huang, Y.-L., Huang, C.-Y., Sastry, S.: Attacks against process control systems: risk assessment, detection, and response. In: The 6th Symposium on Information, Computer and Communications Security, Hong Kong, China, pp. 355–366 (2011)
Chen, Y., Luo, B.: S2a: secure smart household appliances. In: The Second Conference on Data and Application Security and Privacy, San Antonio, TX, USA, pp. 217–228 (2012)
Jokar, P., Nicanfar, H., Leung, V.: Specification-based intrusion detection for home area networks in smart grids. In: International Conference on Smart Grid Communications, Brussels, Belgium, pp. 208–213 (2011)
Ali, Q.I.: Design and implementation of an embedded intrusion detection system for wireless applications. IET Inf. Secur. 6(3), 171–182 (2012)
Alotaibi, B.: A majority voting technique for wireless intrusion detection systems (2016)
Gu, W., et al.: Null data frame: a double-edged sword in IEEE 802.11 WLANs. IEEE Trans. Parallel Distrib. Syst. 21(7), 897–910 (2010)
Kumar, V., et al.: Detection of stealth man-in-the-middle attack in wireless LAN. In: Proceedings of the 2nd IEEE International Conference on Parallel Distributed and Grid Computing (PDGC). IEEE (2012)
Salem, O., Yaning, L., Ahmed, M.: Anomaly detection in medical WSNs using enclosing ellipse and chi-square distance. In: 2014 IEEE International Conference on Communications (ICC). IEEE (2014)
Sbeiti, M., et al.: Paser: secure and efficient routing approach for airborne mesh networks. IEEE Trans. Wirel. Commun. 15(3), 1950–1964 (2016)
Sun, T., Liu, X.: Agent-based intrusion detection and self-recovery system for wireless sensor networks. In: Proceedings of the 5th IEEE International Conference on Broadband Network & Multimedia Technology (IC-BNMT). IEEE (2013)
Wu, K., et al.: hJam: attachment transmission in WLANs. IEEE Trans. Mob. Comput. 12(12), 2334–2345 (2013)
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Latha, P.H., Vasantha, R. (2019). An Efficient Security System in Wireless Local Area Network (WLAN) Against Network Intrusion. In: Silhavy, R. (eds) Software Engineering and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 763. Springer, Cham. https://doi.org/10.1007/978-3-319-91186-1_2
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DOI: https://doi.org/10.1007/978-3-319-91186-1_2
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