Roya Ensafi

h-index19
2papers
1,249citations

2 Papers

13.0CRJan 23, 2019
The Chain of Implicit Trust: An Analysis of the Web Third-party Resources Loading

Muhammad Ikram, Rahat Masood, Gareth Tyson et al.

The Web is a tangled mass of interconnected services, where websites import a range of external resources from various third-party domains. However, the latter can further load resources hosted on other domains. For each website, this creates a dependency chain underpinned by a form of implicit trust between the first-party and transitively connected third-parties. The chain can only be loosely controlled as first-party websites often have little, if any, visibility of where these resources are loaded from. This paper performs a large-scale study of dependency chains in the Web, to find that around 50% of first-party websites render content that they did not directly load. Although the majority (84.91%) of websites have short dependency chains (below 3 levels), we find websites with dependency chains exceeding 30. Using VirusTotal, we show that 1.2% of these third-parties are classified as suspicious --- although seemingly small, this limited set of suspicious third-parties have remarkable reach into the wider ecosystem. By running sandboxed experiments, we observe a range of activities with the majority of suspicious JavaScript downloading malware; worryingly, we find this propensity is greater among implicitly trusted JavaScripts.

18.2CRFeb 25, 2016
Identifying and characterizing Sybils in the Tor network

Philipp Winter, Roya Ensafi, Karsten Loesing et al.

Being a volunteer-run, distributed anonymity network, Tor is vulnerable to Sybil attacks. Little is known about real-world Sybils in the Tor network, and we lack practical tools and methods to expose Sybil attacks. In this work, we develop sybilhunter, the first system for detecting Sybil relays based on their appearance, such as configuration; and behavior, such as uptime sequences. We used sybilhunter's diverse analysis techniques to analyze nine years of archived Tor network data, providing us with new insights into the operation of real-world attackers. Our findings include diverse Sybils, ranging from botnets, to academic research, and relays that hijack Bitcoin transactions. Our work shows that existing Sybil defenses do not apply to Tor, it delivers insights into real-world attacks, and provides practical tools to uncover and characterize Sybils, making the network safer for its users.