A Study on Identity Based Attack Detection and Localization by the Clustering in Wireless Sensor Network
Tuhin Das1
Section:Review Paper, Product Type: Journal Paper
Volume-4 ,
Issue-2 , Page no. 96-99, Feb-2016
Online published on Feb 29, 2016
Copyright © Tuhin Das . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Tuhin Das, “A Study on Identity Based Attack Detection and Localization by the Clustering in Wireless Sensor Network,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.2, pp.96-99, 2016.
MLA Style Citation: Tuhin Das "A Study on Identity Based Attack Detection and Localization by the Clustering in Wireless Sensor Network." International Journal of Computer Sciences and Engineering 4.2 (2016): 96-99.
APA Style Citation: Tuhin Das, (2016). A Study on Identity Based Attack Detection and Localization by the Clustering in Wireless Sensor Network. International Journal of Computer Sciences and Engineering, 4(2), 96-99.
BibTex Style Citation:
@article{Das_2016,
author = {Tuhin Das},
title = {A Study on Identity Based Attack Detection and Localization by the Clustering in Wireless Sensor Network},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2016},
volume = {4},
Issue = {2},
month = {2},
year = {2016},
issn = {2347-2693},
pages = {96-99},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=802},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=802
TI - A Study on Identity Based Attack Detection and Localization by the Clustering in Wireless Sensor Network
T2 - International Journal of Computer Sciences and Engineering
AU - Tuhin Das
PY - 2016
DA - 2016/02/29
PB - IJCSE, Indore, INDIA
SP - 96-99
IS - 2
VL - 4
SN - 2347-2693
ER -
VIEWS | XML | |
1638 | 1397 downloads | 1498 downloads |
Abstract
Wireless sensor networks are most vulnerable to identity based attacks in which malicious device is used to create forged MAC addresses of specified authorized client. The identity of a node can be easily verified through cryptographic authentication techniques which are not always possible because it requires key management and other additional infrastructural overhead. In this paper we propose a system for detecting identity based attacks and also searching the actual positions of adversaries which are responsible for the attacks. Firstly we propose OADL (Attack Detection & Localization) model for identity based attack that utilizes correlation of nodes signal's spatial property (i.e spatial information, a physical property of each node) and the average received signal gain of received signal strength (RSS) collected from each wireless sensor nodes. Then we describe the integration of our attack detection model into our real time localization system, which has the ability to locate the actual positions of the attackers through Partitioning AroundMedoids clustering analysis for localization. We are able to show that the actual positions of the attackers that can be located using localization algorithms. Then we make evaluation based on our model through experimentation using both 802.11 network and 802.15.4 network model. Our results will indicate that identity based attack detection can be achieved with high precision in attack detection rate and localization of multiple adversaries.
Key-Words / Index Term
Identity based attack, localization, OADL model, Received signal strength
References
[1] John Bellardo and Stefan Savage, “802.11 Denial-ofservice attacks: real vulnerabilities and practical solutions”, Proceedings of the 12th conference on USENIX Security Symposium, Vol. 12, pp. 15-28, 2003.
[2] F. Ferreri, M. Bernaschi and L. Valcamonici, “Access Points Vulnerabilities to Dos Attacks in 802.11 Networks”, IEEE Wireless Communications and Networking Conference, Vol. 1, pp. 634-638, 2004.
[3] Martin Eian, “Fragility of the robust security network: 802.11 denial of service”, Applied Cryptography and Network Security: Lecture Notes in Computer Science, Vol. 5536, pp. 400–416, 2009.
[4] Bing Wu, Jie Wu, E.B. Fernandez and S. Magliveras, “Secure and Efficient Key Management in Mobile Ad Hoc Networks”, Proceedings of IEEE International Symposium on Parallel and Distributed Processing, 2005.
[5] Avishai Wool, “Lightweight Key Management for IEEE 802.11 Wireless Lans With Key Refresh and Host Revocation”, Wireless Networks, Vol. 11, No. 6, pp. 677- 686, 2005.
[6] Mathias Bohge and Wade Trappe, “An Authentication Framework for Hierarchical Ad Hoc Sensor Networks”, Proceedings of the 2nd ACM workshop on Wireless security, pp. 79-87, 2003.
[7] M. Demirbas and Youngwhan Song, “An RSSI-based Scheme for Sybil Attack Detection in Wireless Sensor Networks”, International Symposium on a World of Wireless, Mobile and Multimedia Networks, pp. 564–570, 2006.
[8] Daniel B. Faria and David R. Cheriton, “Detecting identitybased attacks in wireless networks using signalprints”, Proceedings of WiSe’06: ACM Workshop on Wireless Security, pp. 43–52, 2006.
[9] Liang Xiao, L. Greenstein, N. Mandayam, and W. Trappe, “Fingerprints in the Ether: Using the physical layer for wireless authentication”, IEEE International Conference on Communications, pp. 4646–4651, 2007.
[10] Liang Xiao, L. Greenstein, N. Mandayam, and W. Trappe, “A Physical Layer Technique to Enhance Authentication for Mobile Terminals”, IEEE International Conference on Communications, pp. 1520–1524, 2008.
[11] Liang Xiao, L. Greenstein, N. Mandayam, and W. Trappe, “MIMO assisted channel-based authentication in wireless networks” 42nd Annual Conference on Information Sciences and Systems, pp. 642–646, 2008.
[12] Yong Sheng, K. Tan Guanling Chen, D. Kotz and A. Campbell, A, “Detecting 802.11 MAC Layer Spoofing R Maivizhi AND S Matilda: detection and localization of multiple spoofing attackers for mobile wireless networks 1118 Using Received Signal Strength”, IEEE 27th Conference on Computer Communications, pp. 1768–1776, 2008.
[13] Liang Xiao, L. Greenstein, N. Mandayam, and W. Trappe, “Using the physical layer for wireless authentication in time-variant channels”, IEEE Transactions on Wireless Communications, Vol. 7, No. 7, pp. 2571–2579, 2008.
[14] Vladimir Brik, Suman Banerjee, Marco Gruteser and Sangho Oh, “Wireless device identification with radiometric signatures”, Proceedings of the 14th ACM international conference on Mobile computing and networking, pp. 116–127, 2008.
[15] Jie Yang, Yingying Chen, W. Trappe and J. Cheng, “Detection and Localization of Multiple Spoofing Attackers in Wireless Networks”, IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 1, pp. 44- 58, 2013.
[16] P. Bahl and V.N. Padmanabhan, “RADAR: An in-Building RF- Based User Location and Tracking System,” Proc. IEEE INFOCOM, vol. 2, Page(s): 775 – 784, 2000
[17] Maurizio A. Spirito, “On the Accuracy of Cellular Mobile Station Location Estimation,” IEEE Transactions On Vehicular Technology,Vol. 50, No. 3, May 2001.
[18] 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
[19] Daniel B. Faria and David R. Cheriton, “DoS and Authentication in Wireless Public Access Networks,” In Proceedings of the First ACM Workshop on Wireless Security (WiSe’02), September 2002
[20] T. Roos, P. Myllymaki, H.Tirri, P. Misikangas, and J.Sievanen, “A probabilistic approach to WLAN user location estimation,” +International Journal of Wireless Information Networks, vol. 9, no. 3, pp.155–164, July 2002.
[21] Mathias Bohge and Wade Trappe, “An Authentication Framework for Hierarchical Ad Hoc Sensor Networks,” IEEE Trans. Ad Hoc Sensor Networks, WiSE’03, September 19, 2003
[22] J. Bellardo and S. Savage, “802.11 Denial-of-Service Attacks: Real Vulnerabilities and Practical Solutions,” Proc. USENIX Security Symp.,pp. 15-28,2003.
[23] F.Ferreri, M.Bernaschi, and L.Valcamonici, “Access Points Vulnerabilities to Dos Attacks in 802.11 Networks,” Proc. IEEE Wireless Comm. And Networking Conf., 2004.
[24] Qing Li and Wade Trappe, “Detecting Spoofing and Anomalous Traffic in Wireless Networks via Forge-
Resistant Relationship,”IEEE Transactions on Information Forensics and Security, Vol. 2, No. 4,December 2007
[25] J. Yang, Y. Chen, and W. Trappe, “Detecting Spoofing Attacks in Mobile Wireless Environments,” Proc. Ann. IEEE Comm. Soc. Conf. Sensor, Mesh and Ad Hoc Comm. and Networks (SECON), 2009.
[26] Yingying Chen, Jie Yang, Wade Trappe and Richard P. Martin, “Detecting and Localizing Identity-Based Attacks in Wireless and Sensor Networks ”IEEE transactions on vehicular technology, vol. 59, no. 5, June 2010