Supercharge Your Innovation With Domain-Expert AI Agents!

A Method for Online Abnormal Discovery of Virtual Assets Based on Data Flow

A virtual asset and anomaly detection technology, applied in the Internet field, can solve problems such as low timeliness and lack of a framework for outlier detection technology based on data streams, so as to prevent user losses, quickly and effectively detect anomalies, and save The effect of memory space

Active Publication Date: 2020-02-18
NAT UNIV OF DEFENSE TECH
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] However, the above-mentioned anomaly detection methods in the first two [1,2] virtual assets are all offline analysis. Offline analysis is based on the analysis of historical data. If abnormal data is found, then trace the abnormal data to find the source of the abnormality. Therefore, the timeliness is very low
[0009] The outliers found by the above-mentioned third [3] anomaly discovery method refer to the outliers in the current sliding window, not the global outliers, and there is no framework for outlier discovery technology based on data flow

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Method for Online Abnormal Discovery of Virtual Assets Based on Data Flow
  • A Method for Online Abnormal Discovery of Virtual Assets Based on Data Flow
  • A Method for Online Abnormal Discovery of Virtual Assets Based on Data Flow

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] A method for online abnormal discovery of virtual assets based on data streams, the specific hardware information of the virtual asset management system is as follows:

[0073] Virtual asset data flow processing cluster: 2 nodes, the node configuration is 4-core CPU, 32G memory, Centos6.564 bit system;

[0074] Behavioral mode computing cluster: 5 nodes, the node configuration is 4-core CPU, 16G memory, Centos6.564 system;

[0075] Virtual asset operation log database: 1 node, the node configuration is 2-core CPU, 8G memory, 2TB hard disk, Centos6.564-bit operating system;

[0076] Behavior pattern library: 1 node, the node configuration is 2-core CPU, 8G memory, 2TB hard disk, and Centos6.564-bit operating system.

[0077] The above-mentioned hardware configuration environment can handle concurrent operations of 1W-level users. The virtual asset data flow processing cluster extracts data summaries from the continuously inflowing data in real time, stores the data sum...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for fining fictitious asset online abnormity based on data flow. The method mainly comprises the steps of data processing, offline analysis and online analysis. The user operant behavior log data flow flows into a data window, and preprocessing is carried out to extract data summaries; a user normal behavior pattern and a user abnormal behavior pattern are regularly mined from the data in a database through a pattern generating algorithm; data in a sliding window is analyzed in real time through a system, and a current behavior pattern is extracted to be matched with the normal behavior pattern and the abnormal behavior pattern in a pattern bank. The data flow technology is applied to finding abnormity of fictitious assets, a fictitious asset online abnormity fining technical frame based on the data base is designed, the system can detect the abnormity faster and more effectively in real time, and therefore user losses are prevented better.

Description

technical field [0001] The invention belongs to the technical field of the Internet, and in particular relates to a method for online abnormal discovery of virtual assets based on data streams. Background technique [0002] The rapid development of the Internet has led to the prosperity of e-commerce, among which the growth of virtual asset transactions is particularly rapid. Virtual assets refer to items that are competitive, persistent, and can be exchanged or bought and sold in the online world, including online banking and online accounts. , online game equipment weapons, virtual currency, etc. [0003] At present, my country has carried out research on eID-based virtual asset management and preservation technology in cyberspace to achieve standardized and unified management of virtual assets. The virtual asset security system comprehensively and accurately records various operations on virtual assets, but how to dig out abnormal transaction behaviors from these recorde...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/2455G06F16/22G06F16/23
Inventor 朱伟辉傅翔贾焰韩伟红李树栋李爱平周斌杨树强黄九鸣全拥邓璐李虎
Owner NAT UNIV OF DEFENSE TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com