Malicious Route Defending Reliable-Data Transmission Scheme for Multi Path Routing in Wireless Network

Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.

• S. Raja Ratna
• R. Ravi

• Attacker
• Dependence
• Jamming
• Malicious.

[1] G. Lin, and G. Noubir, “On link layer denial of service in data wireless
LANs”, Wireless Communications and Mobile Computing, vol. 5, pp.
273–284, May 2004.
[2] Y. Xuan, Y. Shen, N. P. Nguyen, and M. T. Thai, “A trigger
identification service for defending reactive jammers in WSN”, IEEE
Transactions on Mobile Computing, vol. 11, pp. 793 – 806, May 2012
[3] H. Nguyen, T. Pongthawornkamol, and K. Nahrstedt, “Alibi framework
for identifying reactive jamming nodes in wireless lan”, IEEE Globecom
Telecommunication Conference, pp. 1-6, Dec. 2011.
[4] C. Li, H. Dai, L. Xiao, and P. Ning, ”Communication efficiency of antijamming
broadcast in large-scale multi-channel wireless networks”,
IEEE Transactions on Signal Processing, vol. 60, pp. 5281 - 5292 Oct.
2012.
[5] K. Pelechrinis, M. Iliofotou, and S. V. Krishnamurthy, “Denial of
service attacks in wireless networks: the case of jammers”, IEEE
Communications surveys & tutorials, vol. 13, pg. 245-257, May 2011.
[6] G. Noubir, and G. Lin, “Low-power DoS attacks in data wireless lans
and countermeasures”, Mobile Computing and Communications Review,
vol. 7, pp. 29–30, July 2003.
[7] H. Mustafa, X. Zhang, Z. Liu, W. Xu, and A. Perrig, ”Jamming-resilient
multipath routing”, IEEE Transactions on Dependable and Secure
Computing, vol. 9, pp. 852-864, Nov. 2012.
[8] S. R. Ratna, R. Ravi, and B. Shekhar, “An Intelligent Approach based on
Neuro- Fuzzy Detachment Scheme for Preventing jamming Attack in
Wireless Networks”, Journal of Intelligent and fuzzy logic, Doi
10.3233/IFS-141363. ISSN 1064-1246(Print). 1875-8967 Online (in
press), Sep. 2014.
[9] Y. S. Shiu, S. Y. Chang, H.C. Wu, S.C.H. Huang, and H. H. Chen,
“Physical layer security in wireless networks: a tutorial”, IEEE Wireless
Communications, vol. 18, pp. 66-74, April 2011.
[10] Q. Peng, P. C. Cosman, and L. B. Milstein, “Spoofing or Jamming:
Performance Analysis of a Tactical Cognitive Radio Adversary”, IEEE
Journal of selected areas in communications, vol. 29, pp. 903-911, April
2011.
[11] E. Bayraktaroglu, C. King, X. Liu, G. Noubir, R. Rajaraman, and B.
Thapa, “On the performance of IEEE 802.11 under jamming”, Proc.
IEEE Conference on Computer Communications INFOCOM, pp 1265–
1273, Apr. 2008.
[12] W. Xu, K. Ma, W. Trappe, and Y. Zhang, “Jamming Sensor Networks:
Attack and Defense Strategies“, IEEE Networks Special Issue on Sensor
Networks, vol.20, pp. 41-47, May 2006.
[13] E. Setton, X. Zhu, and B. Girod, “Congestion-Optimized Multi-Path
Streaming of Video over Ad Hoc Wireless Networks,” Proc. IEEE Int’l
Conf. Multimedia and Expo (ICME), vol. 3, pp. 1619 – 1622, June 2004.
[14] A. Tsirigos, and Z. J. Haas, “Analysis of Multipath Routing part I: The
Effect on the Packet Delivery Ratio,” Proc. IEEE Trans. Wireless
Comm., vol. 3, pp. 136-146, Jan. 2004.
[15] L. Zhang, Z. Zhao, Y. Shu, and Lei Wang, “Load Balancing of
Multipath Source Routing in Ad Hoc Networks,” Proc. IEEE
International Conference on Communications, vol. 5, pp. 3197 – 3201,
2002.
[16] M. Wilhelm, I. Martinovic, J. Schmitt, and V. Lenders,”Reactive
jamming in wireless networks: How realistic is the threat?”, In
Proceedings of WiSec, pp. 47-52, 2011.
[17] W. Xu, W. Trappe, Y. Zhang, and T. Wood, ”The Feasibility of
Launching and Detecting Jamming Attacks in Wireless Networks”,
MobiHoc 05, pp. 46-57, May 2005.
[18] A. Proano, and L. Lazos,” Packet-Hiding Methods for Preventing
Selective Jamming Attacks”, IEEE Transactions on dependable and
secure computing, vol. 9, pp. 101 - 114, Jan. 2012.
[19] A. Richa, C. Scheideler, S. Schmid, and J. Zhang,”An Efficient and Fair
MAC Protocol Robust to Reactive Interference”, IEEE/ACM
Transactions on Networking, vol. 21, pp. 760 - 771, June 2013.
[20] L. Wang, and A. M. Wyglinski, “A Combined Approach for
Distinguishing Different Types of Jamming Attacks against Wireless
Networks”, IEEE Pacific Rim (PacRim) Conference on
Communications, Computers and Signal Processing, pp. 8019-814, Aug.
2011.
[21] H. Nguyen, T. Pongthawornkamol, and K. Nahrstedt,”Alibi framework
for identifying reactive jamming nodes in wireless LAN”, IEEE Global
Telecommunication Conference (GLOBECOM 2011), pp. 1-6, Dec.
2011.
[22] K. Pelechrinis, M. IIiofotou, and S. Krishnamurthy, “A measurement –
Driven Anti-jamming System for 802.11 Networks”, IEEE/ ACM
Transactions on Networking, vol. 19, pp. 1208-1222, Aug. 2011.