Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulation

TL;DR

This paper critically examines popular web rankings like Alexa, demonstrating their vulnerability to manipulation and proposing Tranco, a more stable and manipulation-resistant ranking system for research use.

Contribution

The paper introduces Tranco, a new web ranking that is more stable and resistant to manipulation, improving the reliability of web research.

Findings

Existing rankings are easily manipulated, even with minimal effort.

Manipulation can significantly alter the composition of top sites.

Tranco offers a more stable and secure alternative for research.

Abstract

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.