Abstract
A serious threat to cognitive radio networks that sense the spectrum in a cooperative manner is the transmission of false spectrum sensing data by malicious sensor nodes. SNR fluctuations due to wireless channel effects complicate handling such attackers even further. This enforces the system to acquire authentication. Actually, the decision maker needs to determine the reliability or trustworthiness of the shared data. In this paper, the evaluation process is considered as an estimation dilemma on a set of evidences obtained through sensor nodes that are coordinated in an underlying wireless sensor network. Then, a likelihood-based computational trust evaluation algorithm is proposed to determine the trustworthiness of each sensor node's data. The proposed procedure just uses the information which is obtained from the sensor nodes without any presumptions about node’s reliability. Numerical results confirm the effectiveness of the algorithm in eliminating malicious nodes or faulty nodes which are not necessarily conscious attackers.
Highlights
One of the main limitations in developing generation networks and new services for the existing networks is bandwidth scarcity
This paper extends our previous work [16] on cooperative spectrum sensing by taking into account the effect of small scale multipath fading on the PU signal which is received at the sensor nodes as well as the effect of presence some SSDF attackers
Besides uncertainty of reported energy that is measured by sensor devices due to multipath fading phenomena and/or their malfunctioning behaviour, it must be considered that a group of malicious nodes may try to misinform the Fusion Center (FC)
Summary
One of the main limitations in developing generation networks and new services for the existing networks is bandwidth scarcity. A serious threat to cognitive radio networks which sense the spectrum in a cooperative manner is the transmission of false spectrum sensing data by malicious secondary nodes In this case, attacker (attackers) through false data injection in CRN database try to fool CRN and stimulate the CR nodes to use channels occupied by PUs or prevents the SUs from using the empty channels. Our proposed method acquires this robustness by developing a soft trust management process among the sensor nodes To this end, the likelihood of the reported observations are deployed to assign a trust factor to each report; the trust factor of a particular report determine the portion of that reported value on the final decision making in FC.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
