Khasawneh, Mahmoud and Agarwal, Anjali (2017) A Secure and Efficient Authentication Mechanism Applied to Cognitive Radio Networks. IEEE Access, 5 . pp. 15597-15608. ISSN 2169-3536
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Official URL: http://dx.doi.org/10.1109/ACCESS.2017.2723322
Abstract
Cognitive radio (CR) has been introduced to accommodate the steady increment in the spectrum demand. Wireless security in cognitive radio network (CRN) is a challenging technical area due to the dynamic and unique characteristics of CRNs. As a cognitive node can dynamically join or leave the spectrum, providing secure communication becomes problematic and requires more investigation. Authentication is a primary security property in wireless networks wherein the identity of a cognitive node is verified before providing access to available resources. In this paper, a two-level authentication scheme for communication in CRN is proposed. Before joining the network, a CR node is validated by obtaining security credentials from an authorized point. The proposed scheme relies on public- and symmetric-key cryptography, instead of using a digital signaturebased approach. It encrypts data between the communicating nodes in order to improve network security in terms of resource availability and accessibility.This mitigates attacks such as Reflection attack, Denial of Service attack and Man-in-the-Middle attack. The scheme has been evaluated and verified in terms of security functionality, its correctness and the performance, which shows less computation and communication requirements.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering |
|---|---|
| Item Type: | Article |
| Refereed: | Yes |
| Authors: | Khasawneh, Mahmoud and Agarwal, Anjali |
| Journal or Publication: | IEEE Access |
| Date: | 4 July 2017 |
| Digital Object Identifier (DOI): | 10.1109/ACCESS.2017.2723322 |
| Keywords: | Authentication, Protocols, Cryptography, Cognitive radio, Wireless sensor networks, Wireless networks |
| ID Code: | 982673 |
| Deposited By: | Danielle Dennie |
| Deposited On: | 29 Aug 2017 14:55 |
| Last Modified: | 18 Jan 2018 17:55 |
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