Detection method for network flow classification abnormity based on DBSCAN
A technology of network traffic and detection method, which is applied in the field of abnormal network traffic classification detection. It can solve the problems of low algorithm accuracy, imprecise extraction of application layer traffic fingerprint features, and preparatory interference of behavior recognition, etc., and achieve the effect of improving detection efficiency.
Pending Publication Date: 2022-04-26
北京赋乐科技有限公司
View PDF0 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
However, this is accompanied by problems such as low algorithm accuracy or imprecise extraction of application-layer traffic fingerprint features.
Furthermore, if the classified data is applied to user behavior recognition, incorrect data classification will interfere with the preparation of behavior recognition, leading to wrong judgments
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0042] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments It is a part of the embodiments of the present disclosure, but not all of them. Based on the embodiments in the present disclosure, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present disclosure.
[0043] In addition, the term "and / or" in this article is only an association relationship describing associated objects, which means that there may be three relationships, for example, A and / or B, which may mean: A exists alone, A and B exist at the same time, There are three cases of B alone. In addition, the character " / " in this article ...
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
Login to View More Abstract
The embodiment of the invention provides a DBSCAN-based network traffic classification anomaly detection method, device and equipment and a computer readable storage medium. The method comprises the following steps: acquiring network message information; classifying the network message information, and extracting network flow features in the classified network message information; detecting the network flow features through a DBSCAN algorithm to obtain normal network flow feature data; the normal network flow feature data comprises existing network flow feature data and newly acquired network flow feature data; and calculating the score of the newly obtained network flow feature data under each feature dimension, and determining whether the current network flow feature data is abnormal or not. In this way, the detection efficiency of the abnormal data is improved.
Description
technical field [0001] Embodiments of the present disclosure generally relate to the field of network traffic anomaly detection, and more specifically, relate to a DBSCAN-based network traffic classification anomaly detection method, device, device, and computer-readable storage medium. Background technique [0002] With the rapid development of the Internet, network traffic is increasing day by day, and a large number of new applications continue to appear. Each application carries a variety of services and functions, making the network environment extremely large, complex and changeable. In modern network management, the demand for fine-grained management of network traffic drives the research and development of network traffic classification technology. Network traffic classification technology can classify network traffic according to application types, which is of great significance to network management, resource allocation, on-demand services, security systems, and ne...
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
Login to View More Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62H04L9/40
CPCH04L63/1416H04L63/1425G06F18/2321
Inventor 陈志恒毕文冲卢永强王翔袁振龙
Owner 北京赋乐科技有限公司