Intelligent home intrusion detection method based on deep learning

A deep learning and smart home technology, applied in neural learning methods, biological neural network models, electrical components, etc., can solve problems such as information leakage, denial of service, and rights bypass, and achieve low false alarm rate, high detection rate, Overcome the slow effect

Active Publication Date: 2017-10-10
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0002] With the rapid development of the Internet of Things technology, IoT products such as smart homes are gradually popularized. However, the security protection capabilities of smart devices are generally weak, the upgrade and maintenance mechanism is not perfect, and the security configuration of smart devices is unreasonable. many security risks
As the country proposes and implements the "Internet +" action plan in recent years, the "Made in China 2025" plan, the construction of smart cities, etc., a large number of smart devices continue to emerge, but the corresponding security measures are not perfect enough, smart home as an emerging Internet of Things applications are moving towards more and more families. Smart home systems include cameras, routers, gateways

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  • Intelligent home intrusion detection method based on deep learning
  • Intelligent home intrusion detection method based on deep learning
  • Intelligent home intrusion detection method based on deep learning

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[0027] Hereinafter, the preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings; it should be understood that the preferred embodiments are only for illustrating the present invention, not for limiting the protection scope of the present invention.

[0028] Reference figure 1 The shown detection flow chart, the smart home intrusion detection method, includes the following steps:

[0029] 101. Initialize and generate an offline system database with empty content. The database includes three sub-databases with labeled training and test data, data screening link parameters, and multi-layer network parameters based on deep learning;

[0030] 102. The smart home system is composed of sensor nodes, routing nodes, servers, clients, etc. The composition of the smart home is as follows figure 2 As shown, the traffic packet capture software is used to capture the tagged traffic data of the smart home home server gateway, the collec...

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Abstract

The invention discloses an intelligent home intrusion detection method based on deep learning, and relates to an online system, in particular to a method combining a fuzzy neural network and deep learning and used for judging whether intrusion behaviors exist in the network or not. According to the method, deep learning and the fuzzy neural network are organically combined, and the problems that an existing intelligent home intrusion detection technology is difficult to process a large amount of high-dimensional data, the false positive rate is high, the false negative rate is high, and the detection rate is low are solved. By means of an offline system, running parameters of the online system are determined, and the online system conducts real-time intrusion detection. Compared with the prior art, the method is an active monitoring model aiming at intelligent home network attack behaviors, and has the advantages of being high in detection rate, low in false negative rate and the false positive rate, high in real-time performance and the like.

Description

Technical field [0001] The invention relates to the field of smart home security, in particular to a multi-layer neural network intrusion behavior detection method based on deep learning. Background technique [0002] With the rapid development of the Internet of Things technology, Internet of Things products such as smart homes have gradually become popular. However, the current security protection capabilities of smart devices are generally weak. The upgrade and maintenance mechanism is not perfect, and the security configuration of smart devices is unreasonable. Many security risks. In recent years, as the country has proposed and implemented the "Internet +" action plan, the "Made in China 2025" plan, and the construction of smart cities, a large number of smart devices have continued to emerge, but the corresponding security measures are not sound enough. Smart home is a new emerging The Internet of Things applications are moving towards more and more homes. Smart home syst...

Claims

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Application Information

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IPC IPC(8): H04L29/06G06N3/08
CPCG06N3/08H04L63/1416
Inventor 胡向东杨柳胡蓉程占喻唐贤伦白银邢有权李秋实
Owner CHONGQING UNIV OF POSTS & TELECOMM
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