Identity Based Attack Detection using Spatial Information in Clusters for Wireless Sensor Network
Keywords:
Identity Based Attack, Wireless Sensor Network, Received Signal Strength, Clustering Algorithm, Localization, OADLAbstract
Wireless Sensor Network is a network of wireless devices which is spatially distributed in autonomous tiny computing devices and equipped with sensors, a wireless radio, a processor, and a power source. Wireless sensor networks are deployed in the physical environment to monitor and gather a wide range of information. Due to its dynamic operational and manhandled mobile devices used it also suffers from lot of network security threats. Mostly identity based attacks for example masquerade uses MAC address of some authorized person through malicious device to get hold of the secret information inside the wireless network which largely affects the performance of the network. Identifying a device appropriately is a massive challenge in network securities domain which can be perfectly executed by using the spatial information, a physical property of wireless sensor node. We propose OADL (Optimized Attack Detection & Localization) model which uses the average received signal gain of received signal strength with spatial information correlation to find out the identity of attacker and again using PAM clustering algorithm for detecting the number of with multiple illegitimate identities and eliminate them. When we have the datasets discovered by support vector machines can be used to localize the exact position of multiple illegitimate identities. Evaluating this technique using both wifi (802.11 network) and zigbee model (802.15.4 network) we are able to determine result that attained more than 90% percent hit rate. Using integrated detection and localization algorithms provide high accuracy for multiple attackers.
References
Yingying Chen, J. Cheng, W. Trappe, Jie Yang, “Detection and Localization of Multiple Spoofing Attackers in Wireless Networks”, IEEE Transactions on Parallel & Distributed Systems (IEEE TPDS), Volume 24, No.1, Pages 44-58, 2013.
Bellardo and S. Savage, “802.11 Denial-of-Service Attacks: Real Vulnerabilities and Practical Solutions”, Proc. USENIX Security Symp., at San Diego, USA pp. 15- 28, August 2003.
D.G.Harkut, M. S.Ali and P.B.Lohiya, "Scheduling Task of Wireless Sensor Network Using Earliest Deadline First Algorithm", International Journal of Scientific Research in Computer Science and Engineering, Vol.2(2), pp.1-6, Apr 2014
Kaur H. and Kaur B, "Selective DDoS Attacks in Application server and Wireless Network – Survey", International Journal of Computer Sciences and Engineering, Vol.4(8), pp.78-80, Aug -2016
Q. Li, W. Trappe, “Relationship-based detection of spoofing-related anomalous traffic in ad hoc networks,” in Proceedings of the Third Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON) at Reston, Virginia, USA, September 2006. ISBN: 1-4244-0626-9.
A. Singh, L.Kaur and K. Singh, "Impact of DDoS Attacks on Different Services Using Various AQM Techniques", International Journal of Computer Sciences and Engineering, Vo.4(4), pp.149-155, Apr -2016
Y. Sheng, K. Tan, G. Chen, D. Kotz, and A.Campbell, “Detecting 802.11 MAC Layer Spoofing Using Received Signal Strength,” Proc. IEEE INFOCOM at Phoenix, Arizona, USA, Apr. 2008. ISBN: 978-1-4244-2219-7.
Y. Chen, W. Trappe and R. P. Martin, “Detecting and Localizing Wireless Spoofing Attacks,” 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, San Diego, CA, pp. 193-202, 2007. ISBN: 1-4244-1268-4.
V. Brik, S. Banerjee, M. Gruteser, and S. Oh, “Wireless Device Identification with Radiometric Signatures,” Proc. 14th ACM Int’l Conf. Mobile Computing and Networking at San Francisco, CA, USA, pp. 116-127, 2008. ISBN: 978-1-60558-096-8
Das T “Identity Based Attack Detection and Localization by the Clustering in Wireless Sensor Network” International Journal of Computer Sciences and Engineering, Vol.-4(2), pp.96-99, Feb 2016. E-ISSN: 2347-2693
P. Bahl and V.N. Padmanabhan, “RADAR: An in-Building RFBased User Location and Tracking System,” Proc. IEEE INFOCOM, Tel Aviv, Israel, pp. 775-784 2000. ISBN: 0-7803-5880-5.
J. Yang and Y. Chen, “A Theoretical Analysis of Wireless Localization Using RF-Based Fingerprint Matching,” Proc. Fourth Int’l Workshop System Management Techniques, Processes and
Services (SMTPS), Miami, Florida USA, pp. 1-6, Apr. 2008.
C. Hsu and C. Lin, “A Comparison of Methods for Multiclass Support Vector Machines,” IEEE Trans. Neural Networks, vol. 13, no. 2, pp. 415-425, Mar. 2002.
ma Korupolu, S Kartik and G Kalyan Chakravarthi, "An Efficient Approach for Secure Data Aggregation Method in Wireless Sensor Networks with the impact of Collusion Attacks", International Journal of Scientific Research in Computer Science and Engineering, Vol.4(3), pp.25-28, Jun 2016.
N. Cristianini and J. Shawe-Taylor, “An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods” Cambridge University Press, NY, USA pp. 1360142, 2000. ISBN 0-521-78019-5.
L. Kaufman and P.J. Rousseeuw, “Finding Groups in Data: An Introduction to Cluster Analysis”, Wiley Series in Probability and Statistics, New York, USA, pp. 131-146, 1990. ISBN: 9780471878766.
P. Bahl and V. N. Padmanabhan, “RADAR: an in-building RF-based user location and tracking system”, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel, pp. 775-784, 2000. ISBN: 0-7803-5880-5
Barapatre M “Spoofing Attack Detection and Localization inAdhoc network using Received Signal Strength (RSS) “ International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 5, pp.6706-6710, May 2014. ISSN: 2278-1021.
M. Bohge and W. Trappe, “An Authentication Framework For Hierarchical Ad Hoc Sensor Networks,” In Proc. ACM Workshop on Wireless Security (WiSe) San Diego, CA, USA, pp. 79–87, 2003. ISBN: 1-58113-769-9
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