Fishing website detection method and device, computing device and computer storage medium

Abstract

The invention discloses a fishing website detection method and device, a computing device and a computer storage medium. The fishing website detection method comprises the following steps: step S1, extracting a plurality of data sources from the web page source code of a website to be detected; performing cross-processing on the plurality of data sources to obtain a keyword group containing a plurality of keywords; step S2, extracting a plurality of registered domain names from the search results obtained by searching with the keyword group as the search criteria; and step S3, detecting whether the website to be detected is a suspicious website or not according to the plurality of registered domain names; and if so, detecting whether the suspicious website is the phishing website or not according to the main domain name corresponding to the plurality of registered domain names. By means of the scheme disclosed by the invention, the keyword group is extracted through performing cross-processing on the plurality of data sources, and the effective keywords of the website to be detected are obtained, therefore, the accuracy of the detecting results is improved; furthermore, it is not required to collect a large amount of sample data, and whether the website to be detected is the phishing website or not can be detected by means of the searched registered domain names, therefore, theinvestment is saved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a detection method, device, computing device and computer storage medium of a phishing website. Background technique [0002] Phishing refers to lure the victim to a fake website disguised as the target website, steal the user's user name, password, certificate number and other personal sensitive information, realize network fraud, and cause the user's personal information to be leaked and financial property to be lost Behavior. In recent years, with the development and popularization of e-commerce, phishing attacks have intensified, so the research on phishing detection technology is urgent. [0003] Currently, phishing detection technologies mainly include blacklist matching, detection methods based on URL features, and machine learning-based phishing detection technologies. However, in the process of realizing the present invention, the inventors have found that there are ...

AI Technical Summary

Problems solved by technology

However, in the process of realizing the present invention, the inventors have found that there are at least the following problems in the prior art: blacklist matching detection technology, usually the blacklist database is not updated in time, which easily leads to missed reports and high false positive rates of new phishing websites The problem of phishing website detection based on URL features, because the detection data source is single, the probability of successfully identifying phishing websites is low; phishing detection technology based on machine learning usually needs to collect a large number of samples before learning the phishing website detection model Data, including a large number of phishing websites and legitimate website samples, and labeling the sample data requires a lot of time, energy and financial resources

And this phishing website detection method based on webpage similarity needs to collect enough legal websites, and needs a large number of calculations, and the detection efficiency is low; At the same time, due to the incomplete collection of legitimate websites, the selection of thresholds is not accurate enough, and the detection results have a high probability of false positives

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