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

A malicious software and detection system technology, applied in transmission systems, electrical components, network data retrieval, etc., can solve problems such as slow response speed of client requests, increase cloud server workload, etc., improve judgment accuracy, ease workload, The effect of improving detection accuracy

Active Publication Date: 2016-03-23
重庆巴陆科技有限公司
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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 i

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

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Embodiment Construction

[0026] In order to make the purpose, technical scheme and advantages of the present invention clearer, detailed implementation and specific operation process are provided, and the present invention will be further described in detail below in conjunction with the accompanying drawings:

[0027] see figure 1 and figure 2 , a malware detection system based on P2P dynamic cloud, including a single solid-state cloud server, several dynamic cloud servers and several distributed terminals. Distributed terminals can be computers, mobile phones or tablets, etc. A P2P network is formed between several dynamic cloud servers, and a C / S network is formed between a single solid-state cloud server and several dynamic cloud servers. The C / S network is composed of type terminals, wherein, the dynamic cloud server is used as the server end, and the distributed terminal is used as the client; the distributed terminal is used for abnormal monitoring of software behavior in the network, obtain...

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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...

Claims

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Application Information

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IPC IPC(8): H04L29/06H04L29/08G06F17/30
CPCH04L63/1416H04L63/145H04L67/1025H04L67/104G06F16/951H04L67/01
Inventor 黄智勇李杰刘越钟成明
Owner 重庆巴陆科技有限公司
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