Abstract: How Unique is Your Onion?

Recent studies have shown that Tor onion (hidden) service websitesare particularly vulnerable to website  fingerprinting attacks due to their limited number and sensitive nature. In this talk, I will present a multi-level feature analysis of onion site fingerprintability, considering three state-of-the-art website  fingerprinting methods and 482 Tor onion services, making this the largest analysis of this kind completed on onion services to date.

Prior studies typically report average performance results for a given website fingerprinting method or countermeasure. We investigate which sites are more or less vulnerable to fingerprinting and which features make them so. We find that there is a high variability in the rate at which sites are classified (and misclassified) by these attacks, implying that average performance figures maynot be informative of the risks that website fingerprinting attacks pose to particular sites. Our results also inform the design of website fingerprinting countermeasures and their evaluation.

Bio:

Rebekah received her PhD from Drexel University in September. She is currently working in the Privacy Security and Automation lab with Dr. Rachel Greenstadt and is beginning a postdoc position at KU Leuven. Rebekah’s research explores developing and applying machine learning methods to privacy and security problems, specifically problems in which there may be distribution differences in the data.