Distinguishing Tor From Other Encrypted Network Traffic Through Character Analysis

Autor:	Choorod, Pitpimon, Bauer, Tobias J., Aßmuth, Andreas
Rok vydání:	2024
Předmět:	Computer Science - Cryptography and Security Computer Science - Machine Learning Computer Science - Networking and Internet Architecture
Zdroj:	Proc of the 15th International Conference on Cloud Computing, GRIDs, and Virtualization (Cloud Computing 2024), Venice, Italy, May 2024, pp. 8-12, ISSN 2308-4294
Druh dokumentu:	Working Paper
Popis:	For journalists reporting from a totalitarian regime, whistleblowers and resistance fighters, the anonymous use of cloud services on the Internet can be vital for survival. The Tor network provides a free and widely used anonymization service for everyone. However, there are different approaches to distinguishing Tor from non-Tor encrypted network traffic, most recently only due to the (relative) frequencies of hex digits in a single encrypted payload packet. While conventional data traffic is usually encrypted once, but at least three times in the case of Tor due to the structure and principle of the Tor network, we have examined to what extent the number of encryptions contributes to being able to distinguish Tor from non-Tor encrypted data traffic. Comment: 5 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2405.09412 Zobrazit plný text záznamu View this record from Arxiv