Content and popularity analysis of Tor hidden services
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Abstract (arXiv)
Tor hidden services allow running Internet services while protecting the location of the servers. Their main purpose is to enable freedom of speech even in situations in which powerful adversaries try to suppress it. However, providing location privacy and client anonymity also makes Tor hidden services an attractive platform for every kind of imaginable shady service. The ease with which Tor hidden services can be set up has spurred a huge growth of anonymously provided Internet services of both types. In this paper we analyse the landscape of Tor hidden services. We have studied Tor hidden services after collecting 39824 hidden service descriptors on 4th of Feb 2013 by exploiting protocol and implementation flaws in Tor: we scanned them for open ports; in the case of HTTP services, we analysed and classified their content. We also estimated the popularity of hidden services by looking at the request rate for hidden service descriptors by clients. We found that while the content of Tor hidden services is rather varied, the most popular hidden services are related to botnets.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Aug 2013.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1.
5 papers.
- 2022The Dark Side of the Language: Pre-trained Transformers in the DarkNetcited by 10
- 2022Shedding New Light on the Language of the Dark Webcited by 5
- 2021SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysiscited by 4
- 2022NBC-Softmax : Darkweb Author fingerprinting and migration trackingcited by 1
- 2023URM4DMU: an user represention model for darknet markets userscited by 0
- 2023URM4DMU: an user represention model for darknet markets users19 Mar 2023
- 2022NBC-Softmax : Darkweb Author fingerprinting and migration tracking15 Dec 2022
- 2022Shedding New Light on the Language of the Dark Web14 Apr 2022
- 2022The Dark Side of the Language: Pre-trained Transformers in the DarkNet14 Jan 2022
- 2021SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis1 Apr 2021