Katharina Kohls (Ruhr-University Bochum), Kai Jansen (Ruhr-University Bochum), David Rupprecht (Ruhr-University Bochum), Thorsten Holz (Ruhr-University Bochum), Christina Pöpper (New York University Abu Dhabi)

Traffic-analysis attacks are a persisting threat for Tor users. When censors or law enforcement agencies try to identify users, they conduct traffic-confirmation attacks and monitor encrypted transmissions to extract metadata—in combination with routing attacks, these attacks become sufficiently powerful to de-anonymize users. While traffic-analysis attacks are hard to detect and expensive to counter in practice, geographical avoidance provides an option to reject circuits that might be routed through an untrusted area. Unfortunately, recently proposed solutions introduce severe security issues by imprudent design decisions.

In this paper, we approach geographical avoidance starting from a thorough assessment of its challenges. These challenges serve as the foundation for the design of an empirical avoidance concept that considers actual transmission characteristics for justified decisions. Furthermore, we address the problems of untrusted or intransparent ground truth information that hinder a reliable assessment of circuits. Taking these features into account, we conduct an empirical simulation study and compare the performance of our novel avoidance concept with existing
approaches. Our results show that we outperform existing systems by 22 % fewer rejected circuits, which reduces the collateral damage of overly restrictive avoidance decisions. In a second evaluation step, we extend our initial system concept and implement the prototype MultilateraTor. This prototype is the first to satisfy the requirements of a practical deployment, as it maintains Tor’s original level of security, provides reasonable performance, and overcomes the fundamental security flaws of existing systems.

View More Papers

Countering Malicious Processes with Process-DNS Association

Suphannee Sivakorn (Columbia University), Kangkook Jee (NEC Labs America), Yixin Sun (Princeton University), Lauri Korts-Pärn (Cyber Defense Institute), Zhichun Li (NEC Labs America), Cristian Lumezanu (NEC Labs America), Zhenyu Wu (NEC Labs America), Lu-An Tang (NEC Labs America), Ding Li (NEC Labs America)

Read More

maTLS: How to Make TLS middlebox-aware?

Hyunwoo Lee (Seoul National University), Zach Smith (University of Luxembourg), Junghwan Lim (Seoul National University), Gyeongjae Choi (Seoul National University), Selin Chun (Seoul National University), Taejoong Chung (Rochester Institute of Technology), Ted "Taekyoung" Kwon (Seoul National University)

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

Distinguishing Attacks from Legitimate Authentication Traffic at Scale

Cormac Herley (Microsoft), Stuart Schechter (Unaffiliated)

Read More