Search for: All records

Online advertisers have been quite successful in circumventing traditional adblockers that rely on manually curated rules to detect ads. As a result, adblockers have started to use machine learning (ML) classifiers for more robust detection and blocking of ads. Among these, AdGraph which leverages rich contextual information to classify ads, is arguably, the state of the art ML-based adblocker. In this paper, we present a4, a tool that intelligently crafts adversarial ads to evade AdGraph. Unlike traditional adversarial examples in the computer vision domain that can perturb any pixels (i.e., unconstrained), adversarial ads generated by a4 are actionable in the sense that they preserve the application semantics of the web page. Through a series of experiments we show that a4 can bypass AdGraph about 81% of the time, which surpasses the state-of-the-art attack by a significant margin of 145.5%, with an overhead of <20% and perturbations that are visually imperceptible in the rendered webpage. We envision that a4’s framework can be used to potentially launch adversarial attacks against other ML-based web applications. 

Transnational Internet performance is an important indication of a country's level of infrastructure investment, globalization, and openness. We conduct a large-scale measurement study of transnational Internet performance in and out of 29 countries and regions, and find six countries that have surprisingly low performance. Five of them are African countries and the last is mainland China, a significant outlier with major discrepancies between downstream and upstream performance. We then conduct a comprehensive investigation of the unusual transnational Internet performance of mainland China, which we refer to as the "Great Bottleneck of China''. Our results show that this bottleneck is widespread, affecting 79% of the receiver--sender pairs we measured. More than 70% of the pairs suffer from extremely slow speed (less than 1~Mbps) for more than 5 hours every day. In most tests the bottleneck appeared to be located deep inside China, suggesting poor network infrastructure to handle transnational traffic. The phenomenon has far-reaching implications for Chinese users' browsing habits as well as for the ability of foreign Internet services to reach Chinese customers.