Funnel: Choking Polluters in BitTorrent File Sharing Communities

Abstract

BitTorrent-based file sharing communities are very popular nowadays. Anecdotal evidence hints that such communi- ties are exposed to content pollution attacks (i.e., publication of ‘false’ files, viruses, or other malware), requiring a moderation effort from their administrators. The size of such a cumber- some task increases with content publishing rate. To tackle this problem, we propose a generic pollution control strategy and instantiate it as a mechanism for BitTorrent communities. The strategy follows a conservative approach: it regards newly published content as polluted, and allows the dissemination rate to increase according to the proportion of positive feedback issued about the content. In contrast to related approaches, the strategy and mechanism avoid the problem of pollution dissemination at the initial stages of a swarm, when insufficient feedback is available to form a reputation about the content. To evaluate the proposed solution, we conducted a set of experiments using a popular BitTorrent agent and an implementation of our mechanism. Results indicate that the proposed approach mitigates the dissemination of polluted content in BitTorrent, imposing a low overhead in the distribution of non-polluted ones.

Publication
IEEE TNSM
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Flavio Santos
UFRGS MSc 2008-2010, UFRGS PhD 2010-2013, now a Data Infrastructure Engineer at Spotify, Sweden