Malicious software detection system based on P2P dynamic cloud and malicious software detection method

Abstract

The invention relates to a malicious software detection system based on P2P dynamic cloud and a malicious software detection method. The system comprises a single solid cloud server, multiple dynamic cloud servers and multiple distributed terminals, wherein the multiple dynamic cloud servers form a P2P network, the single solid cloud server and the multiple dynamic cloud servers form a C / S network, the dynamic cloud servers and the distributed terminals form a C / S network, the distributed terminals are used for monitoring abnormality of software behaviors in the network to acquire abnormal behavior characteristics, and the abnormal behavior characteristics are uploaded to the dynamic cloud servers, the dynamic cloud servers are used for analyzing the abnormal behavior characteristics and feeding back the analysis result to the distributed terminals or the solid cloud server, and the solid cloud server is used for carrying out further analysis on the abnormal behavior characteristics uploaded by the dynamic cloud servers and feeding back the analysis result to the distributed terminals through the dynamic cloud servers. Through the system, load of the cloud servers is mitigated, a speed of response to a client request is improved, and precision of detection on the malicious software is improved.

Description

technical field [0001] The invention relates to the field of malware detection, in particular to a P2P dynamic cloud-based malware detection system and method. Background technique [0002] With the rapid development of information technology, the network has gradually become the main way for people to communicate. However, while the network is disseminating some advanced tools and technologies, malicious software has also begun to appear. Almost all Internet users' computers have been invaded by malicious software without knowing it. Malware has gradually become the main threat to the network. [0003] On December 25, 2014, McAfee released the "McAfee Threat Report for the Third Quarter of 2014", which showed that in the third quarter, McAfee Labs detected more than 307 new threats every minute. , more than 5 per second. This quarter, the number of mobile malware samples increased by 16%, and the number of overall malware surged by 76% year-on-year; the number of ransomwa...

AI Technical Summary

Problems solved by technology

"Cloud security" uses the transmission and computing functions of the Internet to transfer the analysis and computing capabilities originally placed on the client side to the server side. Although it largely makes up for the shortcomings of the traditional virus detection and killing mechanism, it also greatly increases the cloud server. workload, resulting in slow responses to client requests

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