International audienceSuppose you find the same username on different online services, what is the probability that these usernames refer to the same physical person? This work addresses what appears to be a fairly simple question, which has many implications for anonymity and privacy on the Internet. One possible way of estimating this probability would be to look at the public information associated to the two accounts and try to match them. However, for most services, these information are chosen by the users themselves and are often very heterogeneous, possibly false and difficult to collect. Furthermore, several websites do not disclose any additional public information about users apart from their usernames (e.g., discus- sion forums or Blog comments), nonetheless, they might contain sensitive information about users. This paper explores the possibility of linking users profiles only by looking at their usernames. The intuition is that the probability that two usernames refer to the same physical person strongly depends on the "entropy" of the username string itself. Our experiments, based on crawls of real web services, show that a significant portion of the users' profiles can be linked using their usernames. To the best of our knowledge, this is the first time that usernames are considered as a source of information when profiling users on the Internet
Abstract-Users' anonymity and privacy are among the major concerns of today's Internet. Anonymizing networks are then poised to become an important service to support anonymousdriven Internet communications and consequently enhance users' privacy protection. Indeed, Tor an example of anonymizing networks based on onion routing concept attracts more and more volunteers, and is now popular among dozens of thousands of Internet users. Surprisingly, very few researches shed light on such an anonymizing network. Beyond providing global statistics on the typical usage of Tor in the wild, we show that Tor is actually being mis-used, as most of the observed traffic belongs to P2P applications. In particular, we quantify the BitTorrent traffic and show that the load of the latter on the Tor network is underestimated because of encrypted BitTorrent traffic (that can go unnoticed). Furthermore, this paper provides a deep analysis of both the HTTP and BitTorrent protocols giving a complete overview of their usage. We do not only report such usage in terms of traffic size and number of connections but also depict how users behave on top of Tor. We also show that Tor usage is now diverted from the onion routing concept and that Tor exit nodes are frequently used as 1-hop SOCKS proxies, through a so-called tunneling technique. We provide an efficient method allowing an exit node to detect such an abnormal usage. Finally, we report our experience in effectively crawling bridge nodes, supposedly revealed sparingly in Tor.
Fast-flux is a redirection technique used by cyber-criminals to hide the actual location of malicious servers. Its purpose is to evade identification and prevent or, at least delay, the shutdown of these illegal servers by law enforcement.This paper proposes a framework to geolocalize fast-flux servers, that is, to determine the physical location of the fast-flux networks roots (mothership servers) based on network measurements. We performed an extensive set of measurements on PlanetLab in order to validate and evaluate the performance of our method in a controlled environment. These experimentations showed that, with our framework, fast-flux servers can be localized with similar mean distance errors than non-hidden servers, i.e. approximately 100 km. In the light of these very promising results, we also applied our scheme to several active fast-flux servers and estimated their geographic locations, providing then statistics on the locations of "in the wild" fast-flux services.
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