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APT (Advanced Persistent Threat) attack detection method based on big data behavior sequence analysis

A technology of sequence analysis and attack detection, applied to electrical components, transmission systems, etc., can solve the problems of low accuracy and low accuracy of APT attack detection, and achieve the effect of improving accuracy and overcoming threats

Active Publication Date: 2016-01-20
THE PLA INFORMATION ENG UNIV
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Problems solved by technology

For example, the patent No. CN103916406A discloses "An APT attack detection system and method based on DNS log analysis". Low, the accuracy of APT attack detection is not high

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  • APT (Advanced Persistent Threat) attack detection method based on big data behavior sequence analysis
  • APT (Advanced Persistent Threat) attack detection method based on big data behavior sequence analysis
  • APT (Advanced Persistent Threat) attack detection method based on big data behavior sequence analysis

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Embodiment Construction

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0034] Such as figure 1 Shown is a kind of APT attack detection method based on big data behavior sequence analysis disclosed by the present invention, comprising the following steps:

[0035] S101. Detecting the user's operation behavior, and constructing a user operation behavior sequence library;

[0036] When it is necessary to perform network threat detection on the user's operation behavior, firstly, the user's operation behavior is detected, and the de...

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Abstract

The invention discloses an APT (Advanced Persistent Threat) attack detection method based on big data behavior sequence analysis. The method comprises the following steps of detecting an operation behavior of a user, and constructing a user operation behavior sequence database; optimizing the user operation behavior sequence database; extracting a user operation behavior sequence based on a big data method; performing matching analysis on the extracted user operation behavior sequence and a behavior sequence in the user operation behavior sequence database, and outputting a matching result; and analyzing the matching result and outputting a threatening behavior. The APT attack detection method based on the big data behavior sequence analysis provided by the invention can improve the accuracy of threat detection, so as to construct a safe and efficient network active defense system, and effectively overcome the threat of APT attacks on network security.

Description

technical field [0001] The invention relates to the technical field of network threat detection, in particular to an APT (Advanced Persistent Threat, Advanced Persistent Penetration) attack detection method based on big data behavior sequence analysis. Background technique [0002] With the rapid development of network technology, the network scale continues to expand, and information services are widely popularized. Many key services, whether for civilian or military use, rely on the network, resulting in more and more frequent network attacks and making the information security situation increasingly serious. Especially in recent years, advanced persistent penetration attacks (APT attacks, Advanced Persistent Threat) targeting specific targets have posed a huge threat to network security. Aurora attack, Stuxnet virus, Flame virus, and Operation Darkmouse are all typical cases of APT attacks. With the continuous popularization of smart terminals, the threat of APT attacks ...

Claims

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Application Information

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IPC IPC(8): H04L29/06
CPCH04L63/1416
Inventor 张瑞杰郭渊博周会娟马骏张俭鸽琚安康杨奎武贾洪勇张琦
Owner THE PLA INFORMATION ENG UNIV
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