Malware propagation control method and device based on triple correlation graph detection

Abstract

The invention belongs to the technical field of network security control, and in particular relates to a malware propagation control method and device based on ternary correlation graph detection; the method includes acquiring data source information of malware, user nodes, and propagation paths, and performing preprocessing ;Establish the ternary association graph; based on the weight matrix of the edges in the ternary association graph, calculate the scores of malware, propagation paths, and user nodes according to the cross-iteration scoring mechanism; use multiple linear regression scores for unified quantification, and calculate the user node Influence; Based on the score value and the hotspot infection driving mechanism, establish an infectious disease SIHR propagation model, and calculate the driving factors on the propagation state and propagation trend; Nodes are isolated. The invention broadcasts malicious software, effectively cuts off the transmission path of malicious software, and isolates infected users, thereby improving user safety.

Description

technical field [0001] The invention belongs to the technical field of network security control, in particular to the analysis of malware propagation in the Internet, and in particular relates to a method and device for malware propagation control based on ternary correlation graph detection. Background technique [0002] With the rapid development of network technology in the past few decades, malware such as viruses and worms is a serious threat to the reliability, integrity and availability of computers. For example, malware can spread through the Internet and infect millions of computers and mobile phones. Malware often spreads or infects in the network, and will cause huge losses in the network. Therefore, in today's increasingly sophisticated cyberattacks and Internet security threats, the analysis of malware propagation is particularly important. It has a positive effect on the public sector's control of network security and timely detection and resolution of social ...

AI Technical Summary

Problems solved by technology

Some scholars extract different malware characteristics for propagation analysis. The advantage is that they can analyze the malware propagation mode from different angles, so as to predict the malware propagation trend, but they have not extracted the relevant factors.

Some scholars quantify the influence and driving force of malware propagation through network topology, user behavior or propagation path, but the quality of index quantification has a direct impact on the propagation results, and these studies have not provided a suitable method for multiple drivers. multivariate quantification

There are also some scholars who have considered the polymorphism of malicious software. For example, the Chinese invention patent CN108667833A applied by Zhang Yuanchao et al. provides a coupling-based communication system malware propagation modeling and optimal control method, which focuses on simultaneous propagation in computer networks. The one-way coupling between the two malicious software A and B, using the SIS model to establish the respective propagation dynamic models of A and B, although this method has a certain analysis of the propagation dynamics, it lacks the extraction and analysis of multivariate effective features

In addition, malware is a constantly evolving process in the process of spreading, and no effective control measures are provided for the constantly evolving situation

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