Method and system for malware network behavior detection based on access router

Abstract

The invention discloses a method and system for performing malicious software network behavior detection based on an access router. The method comprises the following steps that: a wireless router identifies an accessing mobile terminal, agrees to a networking request of the accessing mobile terminal, starts to capture flow generated by networking of the mobile terminal, transmits the acquired network flow into a flow behavior analysis module, and performs flow-based security detection; a detection model server establishes a detection model through flow data, and stores the detection model; the detection model server periodically updates the flow behavior analysis module accessing the router to enhance security protection of the access router; and the wireless router selects a required detection model, and the detection model starts to process input flow data and outputs a detection result. Through adoption of the method and the system, the problem of high resource consumption of the mobile terminal due to installation of detection programs in the mobile terminal by a user is solved. Meanwhile, the problem of large-scale deployment in actual use is solved.

Description

technical field [0001] The invention relates to a method and a system for detecting malicious software network behaviors based on access routers. Background technique [0002] With the widespread use of mobile terminals, especially the rapid popularization of smart phones, mobile smart terminals have brought great changes to modern society. Since entering the 21st century, we have quickly entered the mobile era. The mobile phone is no longer limited to communication services in the traditional sense, but has become a powerful terminal integrating e-commerce, personal payment, social entertainment and other functions. According to Gartner's report statistics, in 2014, the global mobile phone market has reached 3.5 billion units (including 2.7 billion Android systems), which has exceeded the number of PCs, and it is predicted that by 2015 it will exceed 5 billion units. However, with the popularity of mobile applications and the explosive growth of the number of users, the se...

AI Technical Summary

Problems solved by technology

This technology uses network traffic to detect whether a user has installed malware on a mobile terminal, but this technology only stays at the technical level, and there is no actual carrier that implements this technology to complete the entire detection process

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