Anonymous Communication Networks
Event details
| Date | 24.06.2016 |
| Hour | 15:00 › 17:00 |
| Speaker | Ludovic Barman |
| Location | |
| Category | Conferences - Seminars |
EDIC Candidacy Exam
Exam President: Prof. Bryan Ford
Thesis Director: Prof. J-P Hubaux
Co-examiner: Dr. Philippe Oechslin
Background papers:
Riposte: An anonymous messaging system handling millions of users.
Herd: A Scalable, Traffic Analysis Resistant Anonymity Network for VoIP Systems.
Protecting your daily in-home activity information from a wireless snooping attack.
Abstract
Anonymous communication networks are widely used by individual seeking privacy when communicating with the Internet. Unfortunately, the most widespread anonymous communication network, Tor, is known to be vulnerable to traffic-analysis attacks, putting users at risk. Protecting against this class of attack is costly, and requires compromises either in latency or scalability. To better understand the cost of providing traffic-analysis resistance, we analyze two state-of-the-art solutions that are robust against traffic-analysis, and discuss their shortcomings. We then present a local, medium-cost traffic-analysis attack, which highlights a new threat model. Finally, we present PriFi, a traffic-analysis resistant network with low-latency; we discuss the key differences between PriFi and the two solutions presented, and explain why PriFi provides better protection in the new threat model introduced by the traffic-analysis attack.
Exam President: Prof. Bryan Ford
Thesis Director: Prof. J-P Hubaux
Co-examiner: Dr. Philippe Oechslin
Background papers:
Riposte: An anonymous messaging system handling millions of users.
Herd: A Scalable, Traffic Analysis Resistant Anonymity Network for VoIP Systems.
Protecting your daily in-home activity information from a wireless snooping attack.
Abstract
Anonymous communication networks are widely used by individual seeking privacy when communicating with the Internet. Unfortunately, the most widespread anonymous communication network, Tor, is known to be vulnerable to traffic-analysis attacks, putting users at risk. Protecting against this class of attack is costly, and requires compromises either in latency or scalability. To better understand the cost of providing traffic-analysis resistance, we analyze two state-of-the-art solutions that are robust against traffic-analysis, and discuss their shortcomings. We then present a local, medium-cost traffic-analysis attack, which highlights a new threat model. Finally, we present PriFi, a traffic-analysis resistant network with low-latency; we discuss the key differences between PriFi and the two solutions presented, and explain why PriFi provides better protection in the new threat model introduced by the traffic-analysis attack.
Practical information
- General public
- Free
Contact
- Cecilia Chapuis EDIC