| Reference : Content and popularity analysis of Tor hidden services |
| Scientific congresses, symposiums and conference proceedings : Paper published in a book | |||
| Engineering, computing & technology : Computer science | |||
| http://hdl.handle.net/10993/17182 | |||
| Content and popularity analysis of Tor hidden services | |
| English | |
Biryukov, Alex  [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) > ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)] | |
| Pustogarov, Ivan [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >] | |
| Thill, Fabrice [] | |
| Weinmann, Ralf-Philipp [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >] | |
| Jun-2014 | |
| proceedings of the 2014 IEEE 34th International Conference on Distributed Computing Systems Workshops | |
| IEEE Computer Society | |
| Yes | |
| International | |
| DASec 2014, International Conference on Distributed Computing Systems Workshop (ICDCSW 2014) | |
| 30-06-2014 | |
| IEEE | |
| Madrid | |
| Spain | |
| [en] Tor ; hidden service ; classification ; scanning | |
| [en] 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 39824 hidden service descriptors collected on 4th of Feb 2013: we scanned them for open ports; in the case of 3050 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.We also propose a method for opportunistic deanonymisation of Tor Hidden Service clients. In addtiton, we identify past attempts to track “Silkroad” by consensus history analysis. | |
| Researchers ; Professionals | |
| http://hdl.handle.net/10993/17182 |
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