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Detection method of time-sequence type covert channel based on neural network

A neural network and detection method technology, applied in the field of information security, can solve the problems of no analysis of abnormal data, inability to distinguish hidden channel types, poor versatility, etc.

Inactive Publication Date: 2015-07-01
SUZHOU INST FOR ADVANCED STUDY USTC
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Problems solved by technology

These detection algorithms mainly use statistical methods to analyze the characteristic differences between abnormal data and normal data, and do not analyze the inherent characteristics of abnormal data. Therefore, these detection methods have their own limitations and cannot distinguish the detected hidden channel types. It can only detect specific hidden channels, and its versatility is poor

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  • Detection method of time-sequence type covert channel based on neural network
  • Detection method of time-sequence type covert channel based on neural network
  • Detection method of time-sequence type covert channel based on neural network

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Embodiment Construction

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all the embodiments. 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.

[0048] see Figure 1-4 , the embodiment of the present invention includes:

[0049] A time-series type covert channel detection method based on neural network, the steps comprising:

[0050] ⑴ Processing

[0051] (1) Use the network packet capture tool to obtain and record the time slot data generated by known hidden channels, and obtain N pieces of data from each channel, where N is the number of training samples for each channel.

[0052] (2) Extract the time slot data in each sample by programming , and use t...

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Abstract

The invention discloses a detection method of a time-sequence type covert channel based on a neural network. The method comprises the steps of obtaining three feature values of a time interval sequence including a variable coefficient, similarity and an entropy value according to a time interval between data packages; taking a four-dimensional feature vector consisting of the variable coefficient, the similarity, the entropy value and a channel type is a training sample of the neural network to train; detecting by the neural network to judge whether the communication channel has the convert channel and the belonged type after the neural network is astringed.

Description

technical field [0001] The invention belongs to the technical field of information security, and mainly uses a neural network to detect time-series hidden channels. Background technique [0002] Channel hiding is an information security technology emerging in recent years. It mainly uses the normal communication channel in the network to transmit secret information. Its main feature is its high concealment, and it can easily pass through firewalls, access control and other network security facilities, thus posing a great threat to network information security. [0003] Channel concealment can be divided into two types according to the way it is implemented, one is storage type covert channel, and the other is timing type covert channel. Among them, the storage-type covert channel mainly uses the redundant fields of the protocol to transmit secret information, while the sequential covert channel transmits secret information by changing the sending rate and sending time of ne...

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Application Information

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IPC IPC(8): H04B17/30
Inventor 黄刘生肖汉周明沈瑶杨威
Owner SUZHOU INST FOR ADVANCED STUDY USTC
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