Analyzing TOR Network Data Through Deep Learning

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Hemmatyar, Mohammad Mahdi | 2021

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 54176 (19)
University: Sharif University of Technology
Department: Computer Engineering
Advisor(s): Jafari Siavoshani, Mahdi
Abstract:
Today, we live in an information age where all people can access the vast amount of data in the world by connecting to the Internet.Since the Internet has expanded significantly to share information, some individuals and organizations seek to be able to prevent the possible sabotage of some people by monitoring network users. Analysis of computer network traﬀic is one of the importance issues that many activities have been done in this area. One of the most important questions in traﬀic analysis is to identify the main content of traﬀic on the encrypted network. Numerous studies have shown that the traﬀic of websites visited through the Tor network, including Specific information that identifies the website, That an eavesdropper can use this data to reveal the website the user has visited the main goal in this project is specifically to analyze Tor network traﬀic, And we will try to categorize the traﬀic related to each website in the network with deeplearning tools
Keywords:
Deep Learning ; Tor Network ; Website Fingerprinting ; Classify Network Traffic ; Network Traffic

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