CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Matched-Filter-based Spectrum Sensing for Secure Cognitive Radio Network Communications

by Fatty M. Salem, Maged H. Ibrahim, Ihab A. Ali, I. I. Ibrahim
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 18
Year of Publication: 2014
Authors: Fatty M. Salem, Maged H. Ibrahim, Ihab A. Ali, I. I. Ibrahim
10.5120/15312-4025

Fatty M. Salem, Maged H. Ibrahim, Ihab A. Ali, I. I. Ibrahim . Matched-Filter-based Spectrum Sensing for Secure Cognitive Radio Network Communications. International Journal of Computer Applications. 87, 18 ( February 2014), 41-46. DOI=10.5120/15312-4025

@article{ 10.5120/15312-4025,
author = { Fatty M. Salem, Maged H. Ibrahim, Ihab A. Ali, I. I. Ibrahim },
title = { Matched-Filter-based Spectrum Sensing for Secure Cognitive Radio Network Communications },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 18 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number18/15312-4025/ },
doi = { 10.5120/15312-4025 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:06:18.254231+05:30
%A Fatty M. Salem
%A Maged H. Ibrahim
%A Ihab A. Ali
%A I. I. Ibrahim
%T Matched-Filter-based Spectrum Sensing for Secure Cognitive Radio Network Communications
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 18
%P 41-46
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The increasing demand for wireless communication introduces efficient spectrum utilization challenge. To address this challenge, Cognitive Radio (CR) has emerged as the key technology, which enables opportunistic access to the spectrum. However, security is a very important issue but not well addressed in CR networks. In this paper, we focus on security problems arising from Primary User Emulation (PUE) attacks in CR networks where the selfish or malicious node emulates primary user's signals to prevent other secondary users from accessing that frequency band. Our system is based on the deployment of multiple stages of "helper" nodes, helper nodes in the first stage are stationary, close to primary user and responsible for detecting and authenticating primary user's signal based on matched filter spectrum-sensing technique. However, helper nodes in the next stages are placed within the primary user's coverage area and serve as bridges for forwarding the spectrum status information to enable secondary users to verify the cryptographic signature carried by the helper nodes' signals. Moreover, the effect of PUE attack on the performance of matched-filter-based spectrum-sensing technique is illustrated.

References
  1. Chen, R. , Park, J. , and Reed. J. H. 2008. Defense against primary user emulation attacks in cognitive radio networks. IEEE Journal on Selected Areas in Communications; 26(1):25–37.
  2. Akyildiz, I. F. , Lee, W. , Vuran, M. , and Mohanty, S. 2006. NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Computer Networks; 50(13):2127–2159.
  3. Ulversoy, T. 2010. Software defined radio: Challenges and opportunities. IEEE Communications Surveys & Tutorials; 12: 531 – 550.
  4. Federal Communications Commission. Facilitating opportunities for flexible, efficient, and reliable spectrum use employing spectrum agile radio technologies. ET Docket, (03-108), Dec. 2003.
  5. Bhargavi, D. , and Murthy, C. R. 2010. Performance comparison of energy, matched-filter and cyclostationarity-based spectrum sensing. IEEE Eleventh International Workshop of Signal Processing Advances in Wireless Communications (SPAWC), Marrakech, 1-5.
  6. Cabric, D. , Tkachenko, A. , and Brodersen, R. 2006. Spectrum sensing measurements of pilot, energy, and collaborative detection. Proc. IEEE Military Communication Conference, Washington, D. C. , USA, 1–7.
  7. Pawe?czak, P. 2011. Cognitive Radio: Ten Years of Experimentation and Development. IEEE Communications Magazine; 49(3): 90-100, IEEE DOI: 10. 1109/MCOM. 2011. 5723805.
  8. Akyildiz, I. F. , Lo, B. F. , and Ishnan. , R. B. 2011. Cooperative spectrum sensing in cognitive radio networks: A survey. Physical Communication; 4(1): 40-62. Elsevier DOI: 10. 1016/j. phycom. 2011. 12. 003
  9. Ziafat, S. , Ejaz, W. , and Jamal, H. 2011. Spectrum sensing techniques for cognitive radio networks: Performance analysis. 2011 IEEE MTT-S International Microwave Workshop Series on Intelligent Radio for Future Personal Terminals, 1-4. IEEE DOI: 10. 1109/IMWS2. 2011. 6027191.
  10. Sahai, A. , Hoven, N. ,and Tandra, R. 2004. Some fundamental limits in cognitive radio. In Proceedings of the Allerton Conference on Communication, Control, and Computing, Monticello, Ill, USA.
  11. Cabric, D. , Mishra, S. M. , and Brodersen, R. W. 2004. Implementation issues in spectrum sensing for cognitive radios," in Proceedings of the 38th Asilomar Conference on Signals, Systems and Computers; 1: 772–776.
  12. Jain, S. K. , Bharti, M. R. , and Kumar, A. 2013. Distance based an Efficient Transmit Power Control Scheme in Cognitive Radio System with Multiple Antennas. International Journal of Computer Applications; 72(21): 32-37.
  13. Dhope, T. , Simunic, D. 2012. Performance analysis of covariance based detection in cognitive radio. In Proceeding of 35th Jubilee International Convention MIPRO, Opatija, 737 - 742.
  14. Dhope, T. , Simunic, D. 2011. Hybrid detection method for cognitive radio. 19th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, 1-5.
  15. Dhope, T. , Simunic, D. 2012. Hybrid detection method for spectrum sensing in cognitive radio. 35th Jubilee International Convention MIPRO 2012, 765 - 770.
  16. Chen, R. , and Park, J. M. 2006. Ensuring Trustworthy Spectrum Sensing in Cognitive Radio Networks. IEEE Workshop on Networking Technologies for Software Defined Radio Networks, 110-119.
  17. Haykin, S. . 2001. Communication Systems, Fourth Edition, Wiley.
  18. A. T. S. Committee. ATSC digital television standard (a/53) revision e, with amendments no. 1 and 2,. http://www. atsc. org/cms/, 2006.
  19. Cordeiro, C. , Challapali, K. , and Ghosh, M. 2006. Cognitive phy and mac layers for dynamic spectrum access and sharing of tv bands. In Proceeding of the first international workshop on Technology and policy for accessing spectrum, ACM.
  20. Rappaport, T. S. 2002. Wireless communications principles and practice, Prentice Hall, 2nd edition.
  21. Salem, F. M, Ibrahim, M. H. , and Ibrahim, I. I. 2012. A primary user authentication scheme for secure cognitive TV spectrum sharing. International Journal of Computer Science Issue; 9(4) : 157-166.
  22. Thamizharasan, S. , Saraswady, D. , and Saminadan, V. 2013. Periodicity based Cyclostationary Spectrum Sensing in Cognitive Radio Networks". International Journal of Computer Applications; 68(6):6-9.
  23. Second Report and Order and Memorandum Opinion and Order In the Matter of Unlicensed Operation in the TV Broadcast Bands, Additional Spectrum for Unlicensed Devices Below 900 MHz and in the 3 GHz Band, Federal Communication Commission, Document 08-260, Nov. 14, 2008.
  24. Gennaro, R. , Jarecki, S,. Krawczyk, H. , and Rabin, T. 1996. Robust Threshold DSS Signatures. EURO-CRYPT; Lecture notes in computer science1996; 1070 : 354-371.
Index Terms

Computer Science
Information Sciences

Keywords

Matched Filter Spectrum Sensing Cognitive Radio Networks Primary User Emulation Authentication

Powered by PhDFocusTM