Self-adaptive and self-feedback system for discovering abnormity of fictitious assets and implementation method

A virtual asset and anomaly discovery technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve difficult problems related to virtual assets, such as anomalies

Active Publication Date: 2015-12-02
NAT UNIV OF DEFENSE TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, it is difficult to timely and accurately discover different types of virtual asset-related abnormalities using a single method

Method used

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  • Self-adaptive and self-feedback system for discovering abnormity of fictitious assets and implementation method
  • Self-adaptive and self-feedback system for discovering abnormity of fictitious assets and implementation method
  • Self-adaptive and self-feedback system for discovering abnormity of fictitious assets and implementation method

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Embodiment Construction

[0059] The technical solutions of the present invention will be further described below with reference to the drawings and specific embodiments.

[0060] like figure 1 As shown in the schematic diagram of the network structure of the present invention, an adaptive self-feedback virtual asset abnormal discovery system includes a data acquisition module, an abnormal discovery module, an adaptive learning module, and a self-feedback adjustment module; the data acquisition module is connected to an abnormal discovery module, the abnormal discovery module is respectively connected with the adaptive learning module and the self-feedback adjustment module, and the self-feedback adjustment module is connected with the self-adaptive learning module; wherein, the data acquisition module is responsible for collecting and storing the virtual data generated by the application platform in the network space Asset data; the data acquisition module transmits the virtual asset data to the abnor...

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Abstract

The invention belongs to the field of network and information safety, and discloses a self-adaptive and self-feedback system for discovering abnormity of fictitious assets and an implementation method. The system comprises a data acquisition module, an abnormity discovery module, a self-adaptive learning module, and a self-feedback adjusting module. The data acquisition module is connected with the abnormity discovery module. The abnormity discovery module is connected with the self-adaptive learning module and the self-feedback adjusting module. The self-feedback adjusting module is connected with the self-adaptive learning module. The method mainly comprises steps of data acquisition, abnormity discovery, self-adaptive learning processing, and self-feedback adjusting processing. The system gives full consideration to characteristics that fictitious asset data is in quantity and structure is complex, virtual identities of network users are not unique, and a single abnormity discovery method is in low efficiency, based on a data abnormity judging mechanism of weight summation, effectively restrains detection errors caused by a single abnormity discovery method, so as to improve abnormity discovery precision.

Description

technical field [0001] The invention belongs to the field of network and information security, and in particular relates to an adaptive self-feedback virtual asset anomaly discovery system and an implementation method. Background technique [0002] Virtual assets refer to items that are competitive, persistent and can be exchanged or bought and sold in cyberspace, including online banking, online account numbers, online game equipment and weapons, virtual currency, etc. With the rapid development of Internet applications such as social networks, e-commerce, and online games, the daily work, life, and study of netizens have extended from traditional physical spaces to cyberspace. As of December 2014, the number of netizens in my country reached 649 million, among which the usage rates of online games, online shopping, online payment and other applications reached 56.4%, 55.7%, and 46.9% respectively (see literature [1] for details). It can be seen that the use of virtual ass...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/1815G06F16/83
Inventor 全拥贾焰韩伟红周斌杨树强李爱平黄九鸣李树栋刘斐李虎邓璐傅翔朱伟辉
Owner NAT UNIV OF DEFENSE TECH
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