Tor website fingerprint identification method based on attention mechanism and LSTM
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
A technology of fingerprint identification and attention, which is applied in the field of network security, can solve the problems of low accuracy of fingerprint identification and achieve the effect of preventing over-fitting phenomenon
Pending Publication Date: 2022-06-03
BEIJING UNIV OF POSTS & TELECOMM
View PDF0 Cites 0 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
[0009] Aiming at the deficiencies of the prior art, the present invention provides a Tor website fingerprint identification method based on
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
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
Example Embodiment
[0035] Embodiment 1.
[0036] A Tor website fingerprinting method based on attention mechanism and LSTM, which specifically includes the following steps:
[0037] Step 1. Traffic capture: Use the tcpdump tool to collect access traffic, and label each access traffic to capture the access traffic of the monitored website;
[0038] Step 2: Feature screening: Data preprocessing is performed on the captured access traffic to obtain a sequence of TLS record lengths. The TLS record length is approximated to an integer multiple of 512, symbols are added according to the direction of the data packets, and finally converted into a cell representation sequence, as Input to the website fingerprinting model;
[0039]Step 3. Model construction: Build the input layer, Partition layer, LSTM layer, attention mechanism layer, fusion layer and softmax layer, build a classifier model based on attention mechanism and LSTM, and input the cell representation sequence in step 2 into In the model, t...
Example Embodiment
[0042] Embodiment two,
[0043] This embodiment is an improvement of the previous embodiment, a method for fingerprinting Tor website based on attention mechanism and LSTM, which specifically includes the following steps:
[0044] Step 1. Traffic capture: first set the list of websites to be monitored, and obtain the addresses of the monitored websites, visit the monitored websites in sequence through Tor Browser, visit each website 1000 times, use the tcpdump tool to collect the access traffic, and analyze the Each access traffic is tagged, that is, the website category to which the access traffic belongs, and the access traffic of the monitored website is captured;
[0045] Step 2: Feature screening: perform data preprocessing on the captured access traffic, perform TCP stream reorganization on the TCP data packet sequence, record the length of each TLS record, convert it into a TLS record length sequence, and obtain a TLS record length sequence, Approximate the length of t...
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 discloses a Tor website fingerprint identification method based on an attention mechanism and an LSTM. The method specifically comprises the following steps: step 1, traffic capture; step 2, feature screening; 3, constructing a model; step 4, model training; and step 5, performance evaluation: performing performance evaluation on the trained classifier model by using the test set in the step 4. The invention relates to the technical field of network security. According to the Tor website fingerprint identification method based on the attention mechanism and the LSTM, a cell sequence is extracted to serve as a model input feature based on data features of Tor access traffic, a time feature is extracted from the cell sequence by using a multi-branch LSTM network based on a mode of combining the attention mechanism and the LSTM, and then the attention mechanism is used for performing weight parameter optimization on the time feature, so that the Tor website fingerprint identification method based on the attention mechanism and the LSTM is obtained. Therefore, the influence of the key time characteristics on the website fingerprint identification result is found and highlighted, and the defect that the existing Tor website fingerprint identification accuracy is relatively low is overcome.
Description
technical field [0001] The invention relates to the technical field of network security, in particular to a Tor website fingerprint identification method based on an attention mechanism and LSTM. Background technique [0002] The Onion Router (Tor) is a communication tool that provides anonymity to Internet users. Tor encrypts the content of communication and routing information, not only forwards encrypted traffic through randomly assigned nodes, but also divides traffic data into cells with a fixed length of 512B, and uses anonymity methods such as periodic switching circuits to ensure users Privacy of browsing activity. There are already millions of users who use Tor to visit websites anonymously every day to hide their online activities. [0003] Recurrent neural network is a special type of neural network with self-connection in the field of deep learning, which is suitable for processing time series data. Although RNN performs well in processing time series relations...
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
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to view more 
Login to view more