Primary user emulation attack detection method based on channel multipath delay differences

Abstract

The invention relates to a primary user emulation attack detection method based on channel multipath delay differences. In a present method, when a PUE user can obtain prior information of a PU and has a reconfiguration capability, the detection efficiency greatly decreases. The method provided by the invention is characterized in that channel estimation is carried out to obtain small-scale fading characteristics of channels, and a binary hypothesis detection method is utilized to realize primary user emulation attack detection according to the characteristics. Specifically, the method comprises the steps that: according to a multipath fading model of the channels under a fixed scene, a cognitive radio user utilizes lead code information of the master user to carry out relative operation on received signals and synchronous sequences so as to obtain the multipath delay differences of the channels, then the multipath delay difference of two paths largest in amplitude is selected as a binary hypothesis detection object, and a decision is made. According to the invention, only the lead code information of the primary user is needed, background noise power of the channels are not needed, and normal work is available when the primary user emulation user successfully emulates large-scale and middle-scale fading characteristics of the primary user.

Description

Technical field [0001] The patent of the present invention belongs to the field of cognitive radio security, and relates to a method for detecting a main user simulation attack through a small-scale fading feature of a channel when energy detection and variance detection fail. Background technique [0002] Cognitive radio network (Cognitive Radio Network, CRN) can effectively improve the utilization rate of spectrum resources and alleviate the current increasingly serious problem of spectrum resource tension. Its working principle is that under the condition of not interfering with the normal operation of the authorized user (PrimaryUser, PU) in this frequency band, the sensing user (SecondaryUser, SU) obtains the "spectrum hole" that is the idle spectrum information through spectrum sensing technology and waits for the opportunity Access these spectrum holes to share spectrum resources with the main user. But this working mechanism also introduces a series of new security issue...

AI Technical Summary

Problems solved by technology

The method based on energy detection has the advantages of low computational complexity and easy implementation, such as the energy detection method based on Fenton approximation and Markov inequality, but this method is vulnerable to PUEA attacks, when the primary user emulation user (PUE) is attacking When adjusting the transmit power in the middle, the defense performance will be greatly reduced

Channel feature detection identifies the received signal based on the principle of different channel features between the PU transmitter and the PUE transmitter to the SU. For example, calculating the variance of the received signal can obtain the channel feature of log-normal shadow fading. The advantage of this method is that Insensitive to noise, the disadvantage is high implementation complexity and long detection time

Cooperative detection is based on the detection basis of a single SU. Through cooperation, the overall performance is improved and the instability of single user detection is reduced, but it is easy to bring negative effects such as perception data error attacks.

Fingerprint detection uses features that are difficult to imitate in the primary user signal, such as carrier frequency, phase offset, etc., as detection objects and is trained and classified by machine learning methods. PUE imitation

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