% 
% This file was created by the TYPO3 extension
% bib
% --- Timezone: CEST
% Creation date: 2024-04-19
% Creation time: 16-00-43
% --- Number of references
% 2
% 

@Inproceedings { 2016-mitseva-ccs-fingerprinting,
   title = {POSTER: Fingerprinting Tor Hidden Services},
   year = {2016},
   month = {10},
   day = {24},
   pages = {1766-1768},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-mitseva-ccs-fingerprinting.pdf},
   misc2 = {Online},
   publisher = {ACM},
   booktitle = {Proceedings of the 23rd ACM Conference on Computer and Communications Security (CCS), Vienna, Austria},
   language = {en},
   ISBN = {978-1-4503-4139-4},
   DOI = {10.1145/2976749.2989054},
   reviewed = {1},
   author = {Mitseva, Asya and Panchenko, Andriy and Lanze, Fabian and Henze, Martin and Wehrle, Klaus and Engel, Thomas}
}

@Inproceedings { 2016-panchenko-ndss-fingerprinting,
   title = {Website Fingerprinting at Internet Scale},
   year = {2016},
   month = {2},
   day = {21},
   abstract = {The website fingerprinting attack aims to identify the content (i.e., a webpage accessed by a client) of encrypted and anonymized connections by observing patterns of data flows such as packet size and direction. This attack can be performed by a local passive eavesdropper – one of the weakest adversaries in the attacker model of anonymization networks such as Tor. In this paper, we present a novel website fingerprinting attack. Based on a simple and comprehensible idea, our approach outperforms all state-of-the-art methods in terms of classification accuracy while being computationally dramatically more efficient. In order to evaluate the severity of the website fingerprinting attack in reality, we collected the most representative dataset that has ever been built, where we avoid simplified assumptions made in the related work regarding selection and type of webpages and the size of the universe. Using this data, we explore the practical limits of website fingerprinting at Internet scale. Although our novel approach is by orders of magnitude computationally more efficient and superior in terms of detection accuracy, for the first time we show that no existing method – including our own – scales when applied in realistic settings. With our analysis, we explore neglected aspects of the attack and investigate the realistic probability of success for different strategies a real-world adversary may follow.},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2016/2016-panchenko-ndss-fingerprinting.pdf},
   web_url = {https://www.informatik.tu-cottbus.de/\verb=~=andriy/zwiebelfreunde/},
   publisher = {Internet Society},
   booktitle = {Proceedings of the 23rd Annual Network and Distributed System Security Symposium (NDSS '16), February 21-24, 2016, San Diego, CA, USA},
   event_place = {San Diego, CA, USA},
   event_date = {February 21-24, 2016},
   ISBN = {978-1-891562-41-9},
   DOI = {10.14722/ndss.2016.23477},
   reviewed = {1},
   author = {Panchenko, Andriy and Lanze, Fabian and Zinnen, Andreas and Henze, Martin and Pennekamp, Jan and Wehrle, Klaus and Engel, Thomas}
}