Bayesian model-based pseudo-base station identification method

Abstract

The present invention provides a Bayesian model-based pseudo-base station identification method. The method at least comprises the steps of acquiring, by using a mobile communication terminal, a C1 criterion value and a C2 criterion value of each base station; searching a Bayesian model for feature values that are equal to the C1 criterion value and the C2 criterion value, acquiring a forward weight value and a negative weight value of the feature values, and using the forward weight value and the negative weight value as a forward weight value and a negative weight value of the C1 criterion value and the C2 criterion value; calculating a first probability integration value of the base station according to the forward weight value; calculating a second probability integration value of the base station according to the negative weight value; and determining, according to the first probability integration value and the second probability integration value, whether the base station is a pseudo-base station. The pseudo-base station is identified by using the Bayesian model, so that the identification accuracy rate of the pseudo-base station is improved, and the method lays a reliable foundation for further security processing operation on the pseudo-base station.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to a method for identifying a pseudo base station based on a Bayesian model. Background technique [0002] Pseudo base stations are fake base stations. Pseudo base station equipment is generally composed of a host computer and a laptop computer. Through SMS group senders, SMS senders and other related equipment, mobile phone card information centered on it and within a certain radius can be searched. The base station of the mobile phone company, fraudulently using other people's mobile phone numbers to forcibly send short messages such as fraudulent and advertising promotions to the user's mobile phone. When this type of device is running, the signal of the user's mobile phone is forced to connect to the device, resulting in the failure of the mobile phone to use the services provided by the operator normally and affecting the normal use of mobile phone users. [0003] Whethe...

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Problems solved by technology

[0008] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a method for identifying pseudo base stations based on Bayesian models, which is used to solve the problem of large network traffic, delays, or inability to identify pseudo base stations in the prior art. Issues such as early defense

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