Abstract
Distributed spectrum sensing provides an improvement for primary user detection but leads a new security threat into CR system. The spectrum sensing data falsification malicious users can decrease the cooperative sensing performance. In this paper, we propose a distributed scheme in which the presence and absence hypotheses distribution of primary signal is estimated based on past sensing received power data by robust statistics, and the data fusion are performed according to estimated parameters by Dempster-Shafer theory of evidence. Our scheme can achive a powerful capability of malicious user elimination due to the abnormality of the distribution of malicious users compared with that of other legitimate users. In addition, the performance of our data fusion scheme is enhanced by supplemented nodes’ reliability weight.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cabric, D., Mishra, S.M., Brodersen, R.W.: Implementation Issues in Spectrum Sensing for Cognitive radios. In: Conf. Record of the 38th Asilomar Conf. on Signals, Systems and Computers, vol. 1, pp. 772–776 (2004)
Mishra, S.M., Sahai, A., Brodersen, R.W.: Cooperative Sensing among Cognitive Radios. In: IEEE International Conference on Communications, ICC 2006, pp. 1658–1663 (2006)
Ruiliang, C., Jung-Min, P., Hou, Y.T., Reed, J.H.: Toward Secure Distributed Spectrum Sensing in Cognitive Radio Networks. IEEE Communications Magazine 46, 50–55 (2008)
Ruiliang, C., Jung-Min, P., Kaigui, B.: Robust Distributed Spectrum Sensing in Cognitive Radio Networks. In: IEEE The 27th Conference on Computer Communications, INFOCOM 2008, pp. 1876–1884 (2008)
Kaligineedi, P., Khabbazian, M., Bhargava, V.K.: Secure Cooperative Sensing Techniques for Cognitive Radio Systems. In: IEEE International Conference on Communications, ICC 2008, pp. 3406–3410 (2008)
Stephen, J.S., Sai Shankar, N., Rahul, T., James, T.: Performance of Power Detector Sensors of DTV Signals in IEEE 802.22 WRANs. In: Proceedings of the first international workshop on Technology and policy for accessing spectrum. ACM, Boston (2006)
Peng, Q., Zeng, K., Wang, J., Li, S.: A Distributed Spectrum Sensing Scheme Based on Credibility and Evidence Theory in Cognitive Radio Context. In: IEEE 17th International Symposium on in Personal, Indoor and Mobile Radio Communications, pp. 1–5 (2006)
Rousseeuw, P.J.: Robust Regression and Outlier Detection. John Wiley & Sons, Inc., Chichester (1987)
Huber, P.J.: Robust Statistics. John Wiley & Sons, Inc., Chichester (1981)
Urkowitz, H.: Energy detection of unknown deterministic signals. Proceedings of the IEEE 55, 523–531 (1967)
Mansouri, N., Fathi, M.: Simple counting rule for optimal data fusion. In: Proceedings of 2003 IEEE Conference on in Control Applications, CCA 2003, vol. 2, pp. 1186–1191 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nhan, NT., Koo, I. (2009). A Secure Distributed Spectrum Sensing Scheme in Cognitive Radio. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_75
Download citation
DOI: https://doi.org/10.1007/978-3-642-04020-7_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04019-1
Online ISBN: 978-3-642-04020-7
eBook Packages: Computer ScienceComputer Science (R0)