Internet of Things equipment flow fingerprint identification method and device based on unsupervised clustering
An IoT device, unsupervised clustering technology, applied in neural learning methods, character and pattern recognition, biological neural network models, etc., can solve the problems of multiple labor and economic costs, a large number of training samples, etc., to achieve the effect of accurate identification
Active Publication Date: 2021-06-15
TSINGHUA UNIV
View PDF5 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
However, this method can only be applied to known IoT devices, and requires a large number of labeled training samples. This labeling method requires more human and economic costs.
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
[0025] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
[0026] The method and device for identifying traffic fingerprints of Internet of Things devices based on unsupervised clustering according to embodiments of the present invention will be described below with reference to the accompanying drawings.
[0027] figure 1 It is a schematic flowchart of an unsupervised clustering-based traffic fingerprint identification method for IoT devices provided by an embodiment of the present invention.
[0028] Aiming at this problem, the embodiment of the present invention provides an IoT devic...
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 invention provides an Internet of Things equipment flow fingerprint identification method and device based on unsupervised clustering, and the method comprises the steps: extracting an original feature vector of original flow; calculating the original feature vector through a VAE algorithm to obtain a three-dimensional feature vector after dimension reduction; and performing clustering calculation on the three-dimensional feature vectors through a K-means algorithm, and determining clustering boundaries of different Internet of Things devices so as to perform flow fingerprint identification processing according to the clustering boundaries. Therefore, the unsupervised Internet of Things equipment flow fingerprint identification method is realized, and the method is used for realizing accurate identification of Internet of Things equipment fingerprints in the absence of label data.
Description
technical field [0001] The invention relates to the technical field of network traffic analysis, in particular to a method and device for identifying traffic fingerprints of Internet of Things devices based on unsupervised clustering. Background technique [0002] At present, the number of IoT devices on the Internet is in a stage of rapid growth. With the rapid growth of the Internet of Things market, the security management of the Internet of Things has gradually become a new major challenge in network management. The primary task of solving the security problem of the Internet of Things is how to accurately identify the Internet of Things devices in the network. [0003] Currently, there are two main methods for IoT device identification. One is a method similar to operating system fingerprint identification, which uses specific identifiers in network traffic to identify device information (for example, user-agent in http requests) field). However, since there are far ...
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): H04L29/08H04L29/06H04L12/851G06K9/62G06N3/08
CPCH04L67/12H04L63/0876H04L47/2441G06N3/088G06F18/23213
Inventor 杨家海张世泽王之梁李子木吴建平
Owner TSINGHUA UNIV