Development of secured data transmission using machine learning-based discrete-time partially observed Markov model and energy optimization in cognitive radio networks
The cognitive radio network (CR) is a primary and promising technology to distribute the spectrum assignment to an unlicensed user (secondary users) which is not utilized by the licensed user (primary user).The cognitive radio network frames a reactive security policy to enhance the energy monitorin...
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| Published in: | Neural computing & applications Vol. 32; no. 1; pp. 151 - 161 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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London
Springer London
01.01.2020
Springer Nature B.V |
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| ISSN: | 0941-0643, 1433-3058 |
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| Abstract | The cognitive radio network (CR) is a primary and promising technology to distribute the spectrum assignment to an unlicensed user (secondary users) which is not utilized by the licensed user (primary user).The cognitive radio network frames a reactive security policy to enhance the energy monitoring while using the CR network primary channels. The CR network has a good amount of energy capacity using battery resource and accesses the data communication via the time-slotted channel. The data communication with moderate energy-level utilization during transmission is a great challenge in CR network security monitoring, since intruders may often attack the network in reducing the energy level of the PU or SU. The framework used to secure the communication is using the discrete-time partially observed Markov decision process. This system proposes a modern data communication-secured scheme using private key encryption with the sensing results, and eclat algorithm has been proposed for energy detection and Byzantine attack prediction. The data communication is secured using the AES algorithm at the CR network, and the simulation provides the best effort-efficient energy usage and security. |
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| AbstractList | The cognitive radio network (CR) is a primary and promising technology to distribute the spectrum assignment to an unlicensed user (secondary users) which is not utilized by the licensed user (primary user).The cognitive radio network frames a reactive security policy to enhance the energy monitoring while using the CR network primary channels. The CR network has a good amount of energy capacity using battery resource and accesses the data communication via the time-slotted channel. The data communication with moderate energy-level utilization during transmission is a great challenge in CR network security monitoring, since intruders may often attack the network in reducing the energy level of the PU or SU. The framework used to secure the communication is using the discrete-time partially observed Markov decision process. This system proposes a modern data communication-secured scheme using private key encryption with the sensing results, and eclat algorithm has been proposed for energy detection and Byzantine attack prediction. The data communication is secured using the AES algorithm at the CR network, and the simulation provides the best effort-efficient energy usage and security. |
| Author | Vimal, S. Kalaivani, L. Kaliappan, M. Varatharajan, R. Gao, Xiao-Zhi Suresh, A. |
| Author_xml | – sequence: 1 givenname: S. orcidid: 0000-0002-1467-1206 surname: Vimal fullname: Vimal, S. email: vimal28.05.1984@gmail.com organization: Department of IT, National Engineering College – sequence: 2 givenname: L. surname: Kalaivani fullname: Kalaivani, L. organization: Department of EEE, National Engineering College – sequence: 3 givenname: M. surname: Kaliappan fullname: Kaliappan, M. organization: Department of IT, National Engineering College – sequence: 4 givenname: A. surname: Suresh fullname: Suresh, A. organization: Department of Computer Science and Engineering, Nehru Institute of Engineering and Technology – sequence: 5 givenname: Xiao-Zhi surname: Gao fullname: Gao, Xiao-Zhi organization: School of Computing, University of Eastern Finland – sequence: 6 givenname: R. surname: Varatharajan fullname: Varatharajan, R. organization: Department of Electronics and Communication Engineering, Sri Ramanujar Engineering College |
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| Keywords | Wireless communication Éclat algorithm Cognitive radio networks Byzantine attack Machine learning |
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