Victor Le Pochat (imec-DistriNet, KU Leuven), Tom Van Goethem (imec-DistriNet, KU Leuven), Samaneh Tajalizadehkhoob (Delft University of Technology), Maciej Korczyński (Grenoble Alps University), Wouter Joosen (imec-DistriNet, KU Leuven)

In order to evaluate the prevalence of security and privacy practices on a representative sample of the Web, researchers rely on website popularity rankings such as the Alexa list. While the validity and representativeness of these rankings are rarely questioned, our findings show the contrary: we show for four main rankings how their inherent properties (similarity, stability, representativeness, responsiveness and benignness) affect their composition and therefore potentially skew the conclusions made in studies. Moreover, we find that it is trivial for an adversary to manipulate the composition of these lists. We are the first to empirically validate that the ranks of domains in each of the lists are easily altered, in the case of Alexa through as little as a single HTTP request. This allows adversaries to manipulate rankings on a large scale and insert malicious domains into whitelists or bend the outcome of research studies to their will. To overcome the limitations of such rankings, we propose improvements to reduce the fluctuations in list composition and guarantee better defenses against manipulation. To allow the research community to work with reliable and reproducible rankings, we provide Tranco, an improved ranking that we offer through an online service available at https://tranco-list.eu.

View More Papers

Practical Hidden Voice Attacks against Speech and Speaker Recognition...

Hadi Abdullah (University of Florida), Washington Garcia (University of Florida), Christian Peeters (University of Florida), Patrick Traynor (University of Florida), Kevin R. B. Butler (University of Florida), Joseph Wilson (University of Florida)

Read More

Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks

Michael Rodler (University of Duisburg-Essen), Wenting Li (NEC Laboratories, Germany), Ghassan O. Karame (NEC Laboratories, Germany), Lucas Davi (University of Duisburg-Essen)

Read More

TextBugger: Generating Adversarial Text Against Real-world Applications

Jinfeng Li (Zhejiang University), Shouling Ji (Zhejiang University), Tianyu Du (Zhejiang University), Bo Li (University of California, Berkeley), Ting Wang (Lehigh University)

Read More

A Treasury System for Cryptocurrencies: Enabling Better Collaborative Intelligence

Bingsheng Zhang (Lancaster University), Roman Oliynykov (IOHK Ltd.), Hamed Balogun (Lancaster University)

Read More