An MDP Approach for Defending Against Fraud Attack in Cognitive Radio Networks

ABSTRACT

Cognitive radio networks (CRNs) have been introduced in recent years to solve frequency leakage. In these networks, several challenges such as Lion and jamming attacks, giving false sensing information, low accuracy in detection of primary users, and sensing error can lead to decrease in CRN's performance. Selecting appropriate free bands by secondary users (SUs) can prevent interference and increase frequency use. In this paper, we present a decision making method based on reinforcement learning to find the optimal strategy for SU in best channel selection. In our model, effect of collision fraud and sensing error is considered simultaneously. In the proposed model, to overcome falsification of sensing reports, the abstract of spectrum sensing data falsification attack is extracted and modelled by using model-based reinforcement learning method. We formalize different states of system, actions of SUs, and probability transitions between states in the framework of Markov decision process (MDP). The proposed model is evaluated by numerical results and optimal strategies according to different effective parameters in network performance are studied.

Keywords:

• Cognitive radio
• Secondary users
• MDP
• Fraud attack

Additional information

Notes on contributors

Hadi Shahriar Shahhoseini

Hadi Shahriar Shahhoseini received BS degree in electrical engineering from University of Tehran, in 1990, MS degree in electrical engineering from Azad University of Tehran in 1994, and PhD degree in electrical engineering from Iran University of Science and Technology, in 1999. He is an associate professor of the electrical engineering department in Iran University of Science and Technology. His areas of research include networking, supercomputing, and reconfigurable computing. More than 150 papers have been published from his research works in scientific journals and conference proceedings. He is an executive committee member of IEEE TCSC and serves IEEE TCSC as regional coordinator in Middle-East countries.

E-mail: [email protected]

Amir Hosein Jafari

Amir Hosein Jafari received the BSc degree in electrical engineering in 2005 from Kashan University, and MSc degree in electrical engineering in 2008 from Shiraz University of Technology, Shiraz. He is currently pursuing the PhD degree at Iran University of Science and Technology. His research interests include data communication networking and secure communication, mobile communications, and optical communications.

E-mail: [email protected]

Khadijeh Afhamisisi

Khadijeh Afhamisisi received the PhD degree in electrical engineering in 2013 from Iran University of Science. Her research interests include data communication networking and secure communication and cognitive networks.

E-mail: [email protected]