Paper Titles

Experimental Investigation of Process Parameters in Wire Electrical Discharge Machining by Response Surface Methodology on IS2062 Steel
p.53

Experimental Investigation on Emission Characteristics of Catalytic Converter Using Different Wash Coat Material
p.62

Microstructure and Mechanical Properties of Castings under Vibration Techniques - A Review
p.71

Optimal Design and Planning of an Autonomous Hybrid (Wind/Solar-PV/Diesel/Battery) Power System
p.83

Co-Ordinated most Active Band (MAB) Attack: For Optimum Payoff in Cognitive Radio Networks
p.93

Analysis of EMCA, EFNR and HEFRN Algorithm in Wireless Sensor Networks
p.102

Experimental Investigations with Fuzzy Controller for PV Fed DC Motor Incorporating SEPIC Converter as Efficient Power Interface
p.110

Implementation of Embedded Floating Point Arithmetic Units on FPGA
p.126

Modelling and Simulation of Solar Photovoltaic Cell for Different Insolation Values Based on MATLAB/Simulink Environment
p.137

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 550Co-Ordinated most Active Band (MAB) Attack: For...

Co-Ordinated most Active Band (MAB) Attack: For Optimum Payoff in Cognitive Radio Networks

Article Preview

Abstract:

The unused or under-utilized TV bands are opportunistically utilized by Cognitive Radio enabled IEEE 802.22 Wireless Regional Area Networks (WRAN). However due to the nature of cognitive radio networks and lack of proactive security protocols, these networks are vulnerable to various Denial of Service (DoS) threats. In this paper the target band chosen for attack is a specific band called as Most Active Band (MAB) which has most signal activities among the available bands. Co-ordination among the malicious nodes in MAB is analyzed to produce maximum net outcome. Simulation results are provided to demonstrate the effectiveness of the proposed co-ordinated MAB attack.

You might also be interested in these eBooks

Mechanical and Power Research

Info:

Periodical:

Applied Mechanics and Materials (Volume 550)

Pages:

93-101

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.550.93

Citation:

Cite this paper

Online since:

May 2014

Authors:

R. Sabitha*, K.R. Shankar Kumar, Christo Raj. V. Reegan, S. Dinesh

Keywords:

Cognitive Cooperation, Cognitive Radio (CR), Denial of Service (DoS) Attack, Most User Band Attack

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] F. C. C. Spectrum policy task force report, IEEE Trans. Information Forensics and Security. p.02–155, (2002).

[2] F. C. C. 2008. In the matter of unlicensed operation in the TV broadcast bands. Second Report and Order and Memorandum Opinion and Order. 08-260A1, (2008).

[3] Bazelon.C. 2008. Licensed or unlicensed: The economic considerations in incremental spectrum allocations. New Frontiers in Dynamic Spectrum Access Networks, 2008. IEEE Symposium 3: p.1–8, (2008).

DOI: 10.1109/dyspan.2008.66

[4] Tai-hoon Kim, Wai-Chi Fang, Carlos Ramos, Sabah Mohammed, Osvaldo Gervasi, Adrian Stoica, Ubiquitous Sensor Networks and its applications, 1-3, (2012).

[5] Mitola, J. and J. Maguire, G.Q. 1999. Cognitive Radio: making software radios more personal. Personal Communications, IEEE 6: p.13–18, (1999).

DOI: 10.1109/98.788210

[6] Akyildiz I.F. 2006. Next generation/dynamic spectrumaccess/cognitive radio wireless networks: a survey. Computer Networks 50: 2127–2159, (2006).

DOI: 10.1016/j.comnet.2006.05.001

[7] F.H. Tseng, LD Chou, HC Chao, A survey of black hole attacks in wireless mobile ad hoc networks. Human-centric Computing and Information Sciences 1 (1), 1-16, (2011).

DOI: 10.1186/2192-1962-1-4

[8] Stevenson C.R. IEEE 802. 22: The first cognitive radio wireless regional are network standard. IEEE Communication Magazine, (2009).

[9] IEEE 802. 22 WG. 2006. IEEE p.802. 22/d0. 1 draft standard for wireless regional area networks part 22: Cognitive wireless ran medium access control (MAC) and physical layer (PHY) specifications: Policies and procedures for operation in the TV bands, (2006).

DOI: 10.1109/ieeestd.2011.5951707

[10] Nasai Hu, Yu-DongYao, and Joseph Mitola. 2012. Most Active Band (MAB) attack and countermeasures in a cognitive radio network. IEEE Transactions on Wireless Communications 11: pp.898-902, (2012).

DOI: 10.1109/twc.2012.011812.110927

[11] Shafiullah Khan, Kok-Keong Loo, Noor Mast, TahirNaeem. SRPM: Secure Routing Protocol for IEEE 802. 11 Infrastructure Based Wireless Mesh Networks. J. Network Syst. Manage. 18(2): pp.190-209, (2010).

DOI: 10.1007/s10922-009-9143-3

[12] Bian. K and J. -M. J. Park. 2008. Security vulnerabilities in IEEE 802. 22, WICON '08. Proceedings of the Annual International Conference on Wireless Internet 4: p.1–9, (2008).

[13] Clancy. T and N. Goergen. Security in cognitive radio networks: Threats and mitigation. International Conference on, Cognitive Radio Oriented Wireless Networks and Communications 3: p.1–8, (2008).

DOI: 10.1109/crowncom.2008.4562534

[14] Chen. R, J. -M. Park, and K. Bian. Robust distributed spectrum sensing in cognitive radio networks. IEEE INFOCOM. p.1876 –1884, (2008).

DOI: 10.1109/infocom.2008.251

[15] Chen. R and J. -M. Park. Ensuring trustworthy spectrum sensing in cognitive radio networks. IEEE Workshop on Networking Technologies for Software Defined Radio Networks 1: p.110–119, (2006).

DOI: 10.1109/sdr.2006.4286333

[16] Myerson R.B. Game Theory: Analysis of Conflict. Harvard University, (1997).

[17] Yi Tan, Sengupta. S and Subbalakshmi, K.P. 2011. Analysis of Coordinated Denial-of-service Attacks in IEEE 802. 22 Networks. Selected Areas in Communications, IEEE Journal 29: pp: 890-902, (2011).

DOI: 10.1109/jsac.2011.110419

[18] Sengupta.S. 2008. A game theoretic framework for distributed self-coexistence among IEEE 802. 22networks. In proceedings of IEEE Global Communications Conference (GLOBECOM), (2008).

DOI: 10.1109/glocom.2008.ecp.598