Classification of Service Types using Website Fingerprinting in Anonymous Encrypted Communication Networks


KIPS Transactions on Computer and Communication Systems, Vol. 11, No. 4, pp. 127-132, Apr. 2022
https://doi.org/10.3745/KTCCS.2022.11.4.127,   PDF Download:
Keywords: TOR Network, Machine Learning, Website Fingerprinting, Service Types, Classification
Abstract

An anonymous encrypted communication networks that make it difficult to identify the trace of a user’s access by passing through several virtual computers and/or networks, such as Tor, provides user and data privacy in the process of Internet communications. However, when it comes to abuse for inappropriate purposes, such as sharing of illegal contents, arms trade, etc. through such anonymous encrypted communication networks, it is difficult to detect and take appropriate countermeasures. In this paper, by extending the website fingerprinting technique that can identify access to a specific site even in anonymous encrypted communication, a method for specifying and classifying service types of websites for not only well-known sites but also unknown sites is proposed. This approach can be used to identify hidden sites that can be used for malicious purposes.


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Cite this article
[IEEE Style]
D. Koo, "Classification of Service Types using Website Fingerprinting in Anonymous Encrypted Communication Networks," KIPS Transactions on Computer and Communication Systems, vol. 11, no. 4, pp. 127-132, 2022. DOI: https://doi.org/10.3745/KTCCS.2022.11.4.127.

[ACM Style]
Dongyoung Koo. 2022. Classification of Service Types using Website Fingerprinting in Anonymous Encrypted Communication Networks. KIPS Transactions on Computer and Communication Systems, 11, 4, (2022), 127-132. DOI: https://doi.org/10.3745/KTCCS.2022.11.4.127.