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Section: New Results
Filtering and blocking the Internet
Participants : Mohamed Ali Kaafar, Abdelberi Chaabane, Mathieu Cunche, Cédric Lauradoux, Amrit Kumar.
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Based on 600GB leaked logs from appliances used to filter Internet traffic in Syria, we performed an analysis of the Syrian censorship apparatus. This study have been published in ACM Internet Measurement Conference [7] .
We found that the Internet traffic in Syria was filtered in several ways using IP addresses, domain names and keywords. Content sharing, instant messaging and proxy technologies were heavily censored. Some social media such as badoo.com were fully censored, but others such as Facebook are only censored for specific political and religious pages. We also found evidences of successful usage of censorship-circumvention techniques such as Tor and VPN. We also found that P2P file-sharing and Google cache were used to escape censorship blockage.
While our work might help organizations on both sides of the censorship line, we believe the presented results can help understand the underlying technologies, policies and can inform the design of tools designed to evade the censorship.
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Attacking filters Many major Internet companies use probabilistic techniques to filter the users requests or to prevent malicious attacks. In our work [35] , [34] , we show how they can be polluted/saturated using pre-image attacks and how it increases the false-positive probability. Then, we show how to forge false-positives to mount attacks. In the adversarial settings, we have the liberty to assume that the inputs to the filter are non uniformly distributed. This observation leads to our second contribution: we compute the worst case false-positive probability and obtain new equations for Bloom filter parameters. To support our contributions, we provide four attacks on software applications based on Bloom filter: Bloom-enabled Scrapy web spider, Bitly Dablooms spam filter, Squid web cache and Google Safe Browsing. Our attacks retain some form of DoS. They are all based on the forgery of Uniform Resource Locators (URLs) matching certain pre-image or second pre-image property. The impact of our attack ranges from denial-of-service to massively distributed denial-of-service with reflection.