The most widely used technique for IP geolocation consists in building a database to keep the mapping between IP blocks and a geographic location. Several databases are available and are frequently used by many services and web sites in the Internet. Contrary to widespread belief, geolocation databases are far from being as reliable as they claim. In this paper, we conduct a comparison of several current geolocation databases -both commercial and free-to have an insight of the limitations in their usability.First, the vast majority of entries in the databases refer only to a few popular countries (e.g., U.S.). This creates an imbalance in the representation of countries across the IP blocks of the databases. Second, these entries do not reflect the original allocation of IP blocks, nor BGP announcements. In addition, we quantify the accuracy of geolocation databases on a large European ISP based on ground truth information. This is the first study using a ground truth showing that the overly fine granularity of database entries makes their accuracy worse, not better. Geolocation databases can claim country-level accuracy, but certainly not city-level.

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

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As the Internet struggles to cope with scalability, mobility, and security issues, new network architectures are being proposed to better accommodate the needs of modern systems and applications. In particular, Content-Oriented Networking (CON) has emerged as a promising next-generation Internet architecture: it sets to decouple content from hosts, at the network layer, by naming data rather than hosts. CON comes with a potential for a wide range of benefits, including reduced congestion and improved delivery speed by means of content caching, simpler configuration of network devices, and security at the data level. However, it remains an interesting open question whether or not, and to what extent, this emerging networking paradigm bears new privacy challenges. In this paper, we provide a systematic privacy analysis of CON and the common building blocks among its various architectural instances in order to highlight emerging privacy threats, and analyze a few potential countermeasures. Finally, we present a comparison between CON and today's Internet in the context of a few privacy concepts, such as, anonymity, censoring, traceability, and confidentiality.Further, endpoint authentication mechanisms (whereby an endpoint can only authenticate the counterpart, but not the message) have been challenged by frequent attacks against SSL [34,42] and the hacking of certification authorities [46]. Also, the Internet today often struggles with mobility and resilience to disruption. Transport layer is, by design, unable to manage mobile parties and addon features -e.g., Mobile IPv6 (MIPv6) and Hierarchical MIPv6 [19] -have been suggested, albeit suffering from handoff latency and packet losses [26].Motivated by these issues, new architectures have been proposed, in the last few years, aiming to redesign the Internet (see, e.g., NSF's Future Internet Architecture multi-million program [57]), and accommodate content-oriented applications. In particular, Content-Oriented Networking (CON) [22] has set to decouple contents from hosts, at the network layer, by relying on the publish/subscribe paradigm. CON shifts identification from host to content, so that this can be located anywhere in the network. The content-centric communication paradigm introduced by CON relies on naming the content itself, rather than its location, and thus radically changes the way data is handled. Content is selfcontained, has a unique name, can be retrieved by means of an interest for that name, cached in any arbitrary location, and digitally signed to ensure its integrity and authenticity.

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In this paper we investigate the risk of privacy leakage through mobile analytics services and demonstrate the ease with which an external adversary can extract individual's profile and mobile applications usage information, through two major mobile analytics services, i.e. Google Mobile App Analytics and Flurry. We also demonstrate that it is possible to exploit the vulnerability of analytics services, to influence the ads served to users' devices, by manipulating the profiles constructed by these services. Both attacks can be performed without the necessity of having an attacker controlled app on user's mobile device. Finally, we discuss potential countermeasures (from the perspectives of different parties) that may be utilized to mitigate the risk of individual's personal information leakage.

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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.