Identification method of harassment number

Abstract

The invention discloses an identification method of a harassment number. The identification method of the harassment number comprises the steps of selecting a plurality of harassment numbers and non-harassment numbers which are confirmed; calculating communication behavior indexes of the harassment numbers and non-harassment numbers within a period of time; then forming a training sample set by using the harassment numbers and non-harassment numbers as well as the communication behavior indexes thereof so as to build a random forest classification model, wherein the input of the random forest classification model is the communication behavior index of each user number and the output thereof is a prediction probability of judging each user number as a harassment number or non-harassment number by all the decision-making trees; and inputting the communication behavior index of a to-be-identified number within a period of time into the random forest classification model, calculating the prediction probability of judging the to-be-identified number as a harassment number or non-harassment number by all the decision-making trees, and accordingly determining whether the to-be-identified number is a harassment number. The identification method of the harassment number is belongs to the technical field of network communication, can efficiently identify harass numbers from massive traffic data of the present network by making full use of calling features of calling and called numbers.

Description

technical field [0001] The invention relates to a method for identifying a nuisance number, which belongs to the technical field of network communication. Background technique [0002] Harassing phone calls mainly promote advertising content and fraudulent information, and have become an illegal occupation that disrupts social stability. Through comprehensive analysis, harassing calls generally have the following characteristics: [0003] 1. The called is scattered, and the harassing number calls out multiple numbers per unit time, the frequency is high, and the correlation between the called numbers is small; [0004] 2. The correlation between harassing calls and callees is usually weak, that is, there is little historical call relationship, and the number of calls made by harassing numbers as callers is far greater than the number of calls; [0005] 3. The call duration of harassing calls is usually short, and the called party has a high probability of hanging up; [0...

AI Technical Summary

Problems solved by technology

[0003] 1. The called is scattered, and the harassing number calls out multiple numbers per unit time, the frequency is high, and the correlation between the called numbers is small;

[0004] 2. The correlation between harassing calls and callees is usually weak, that is, there is little historical call relationship, and the number of calls made by harassing numbers as callers is far greater than the number of calls;

[0005] 3. The call duration of harassing calls is usually short, and the called party has a high probability of hanging up;

This technical solution only involves counting the call time interval, call duration, and the number of incoming calls to identify nuisance numbers. Effective identification of nuisance numbers in traffic data

Images