The present invention discloses a method, apparatus, and
system for identifying
Web application types based on multi-dimensional digital features. First, by automatically extracting keywords and mapping multi-dimensional vectors from the content of two dimensions, namely the Web response
page Header and Body fields, the automatic extraction of
Web page digital features is achieved. Secondly, a digital feature
fingerprint benchmark
library for Web applications is constructed, generating benchmark center point vectors, detection radii, and result validity evaluation F1 scores for the Headers and Body fields of Web pages of known application types. The
fingerprint recognition result is obtained by comparing the digital features of different dimensions of the
Web page with the digital feature benchmark
library. Finally, based on the comparison of the sizes of the result validity F1 scores, the
fingerprint recognition results of the multi-dimensional digital features are merged to determine the final
fingerprint recognition result. The present invention realizes the automatic generation of digital feature fingerprints for Web applications, getting rid of the pain point of the difficult
manual extraction of fingerprint rules in conventional methods.