Two-dimensional code risk identification method and system

Abstract

The invention relates to a technical scheme of two-dimensional code risk identification. In the scheme, a set of fraudulent two-dimensional code recognition algorithm is established from multiple dimensions, so that the fraudulent or malicious two-dimensional code can be accurately found in the two-dimensional code provided by the user. According to the scheme, a URL corresponding to a two-dimensional code is identified to identify a malicious URL. The scheme also comprises a derivation risk identification step which comprises deriving and discovering more fraudulent persons and fraudulent persons based on the discovered fraudulent two-dimensional code so as to realize self-circulation two-dimensional code risk identification.

Description

technical field [0001] This application relates to the technical field of information security, and in particular to a method and system for risk identification of two-dimensional codes. Background technique [0002] The appearance of two-dimensional codes greatly facilitates people's lives. They can scan codes to pay, add friends, and open web pages, which greatly reduces the difficulty of people's operations and saves operation time. With the development of information technology, more and more offline scenes are connected online through QR codes, and people have become accustomed to scanning codes. While the QR code brings convenience to people, it also conceals some information, allowing criminals to take advantage of it, thus causing many hidden safety risks. For example, black products will convert phishing links into QR codes for users to scan, thus increasing the difficulty of user identification. Compared with an unknown link, it is easier for users to take the bai...

AI Technical Summary

Problems solved by technology

QR codes not only bring convenience to people, but also cover up some information, allowing criminals to take advantage of them, thus causing many hidden dangers of security risks

[0003] Currently common security scanning solutions include, for example, relying on the blacklist mechanism, but this solution lacks the risk identification capability for QR codes that are not in the blacklist, and also includes post-event and strong confrontation control solutions based on user reports, but these solutions are far from meeting the risk identification requirements for QR codes

[0004] In addition, the current detection methods for malicious URLs corresponding to QR codes are all based on string matching methods. Security vendors collect a large number of malicious URLs and store them in the signature database. When URL detection is performed, only string comparison is performed. This current method can solve most of the malicious URL detection problems, but due to the variability of the URL format mentioned above, a simple change of a malicious URL, without changing the nature of its malicious link, its content has already changed. It is not completely consistent with the features in the virus database to be matched, which makes it impossible to recognize the malicious URL corresponding to the QR code

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