Malicious code generator identification method and system based on software structure clustering

Abstract

The invention provides a malicious code generator identification method and system based on a software structure cluster. The malicious code generator identification method comprises the steps that samples with the same timestamp are found, software structure information structure vectors of the samples with the same timestamp are extracted, Simhash values are calculated, the samples with Simhash distances smaller than an assigned value are found, in this way, the fact that the samples of the class have similar file structures can be judged, and codes are generated for a malicious code generator. The invention further provides a corresponding system structure. Through the method, the generator can be found by using the difference of the generator and a software structure generated through compilation, and the samples with the similar software structure can be found by using large-scale similarities.

Description

technical field [0001] The invention belongs to the technical field of computer network security, in particular to a method for identifying malicious code generators based on software structure clustering. Background technique [0002] The continuous development of computer networks has also promoted the development and evolution of malicious codes. The development and use of malicious codes has become increasingly clear. Many malicious codes, especially remote control tools, control servers, domain names, and some versions, are configurable. This is The work done by malicious code generators. Malicious code generators make it easy to write malicious code, thus resulting in the generation of a large amount of malicious code, endangering users in the network. Contents of the invention [0003] The invention provides a malicious code generator identification method and system based on software structure clustering, which can effectively identify the malicious code generated...

AI Technical Summary

Problems solved by technology

Malicious code generators make it easy to write malicious code, thus resulting in the creation of large amounts of malicious code, endangering users in the network

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