Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Real-time data flow anomaly detection method and system

An anomaly detection and data flow technology, applied in digital data information retrieval, neural learning methods, electrical digital data processing, etc., can solve the problems of non-automation, low detection accuracy of abnormal data, etc., and achieve the effect of sensitive detection

Pending Publication Date: 2021-08-13
福建省海峡信息技术有限公司
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] The purpose of the present invention is to provide a real-time data flow abnormality detection method and system, based on the online sequence memory algorithm of hierarchical time memory to perform real-time abnormality detection on the data flow, so as to solve the problems of existing data flow abnormality detection that cannot be automated, The problem of low accuracy of abnormal data detection

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
  • Real-time data flow anomaly detection method and system
  • Real-time data flow anomaly detection method and system
  • Real-time data flow anomaly detection method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] The technical solution of the present invention will be specifically described below with reference to the accompanying drawings.

[0035] A real-time data flow abnormality detection method, including the following steps:

[0036] First, a real-time data stream, configured the contextual relationship of the data stream through the HTM network, and gives the preliminary evaluation result based on the abnormal conditions of this analysis;

[0037] Secondly, the error statistics are given to the initial assessment results, and the error probability model modeling is performed on the relevant error statistics;

[0038] Finally, combined with the initial assessment results and the error statistical results evaluation data stream normal or not, construct an exception probability detection model.

[0039] The present invention also provides a real-time data flow abnormality detection system, including:

[0040] HTM network module, used to initially detect abnormal data streams, an...

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 relates to a real-time data flow anomaly detection method and system. The method comprises the following steps: firstly, for a real-time data stream, constructing a context relationship of the data stream through an HTM network, and on the basis of an abnormal condition of the analysis data, giving a preliminary evaluation result; secondly, giving error statistics for the preliminary evaluation result, and carrying out error probability model modeling on the related error statistics result; and finally, evaluating whether the data flow is normal or not by combining a preliminary evaluation result and an error statistical result, and constructing an abnormal probability detection model. According to the invention, real-time anomaly detection is carried out on the data stream based on an online sequence memory algorithm of hierarchical time memory, so that the problems of non-automation and low abnormal data detection accuracy in the existing data stream anomaly detection are solved.

Description

Technical field [0001] The present invention relates to a real-time data flow abnormality detection method and system. Background technique [0002] The development of computers and Internet technology has provided more and more users, and at the same time, security issues on the user's computer system are also increasingly concerned. In order to solve this problem, it is increasingly proposed by more and more scenarios for abnormal data stream attack detection methods. Patent [1] pre-training anomaly detection model, based on the data interval corresponding to the respective nodes included in the abnormality detection model, the service data is classified to determine the node corresponding to the data section falling in the service data, as the target node. Then, the position information of the target node in the tree structure corresponding to the abnormality detection model is determined, as the position information corresponding to the service data in the exception detection...

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
IPC IPC(8): G06F16/2455G06F16/2458G06F30/27G06N3/08G06F111/08
CPCG06F16/24568G06F16/2462G06F30/27G06N3/088G06F2111/08
Inventor 张章学叶松唐敏蓝友枢许敦英陈雨婕
Owner 福建省海峡信息技术有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com