32 citations · 87 across the 12 of their papers we have counts for
10 papers · 1 filter
Privacy-Preserving XGBoost Inference
Xianrui Meng, Joan Feigenbaum
Although machine learning (ML) is widely used for predictive tasks, there are important scenarios in which ML cannot be used or at least cannot achieve its full potential. A major…
PriFi: Low-Latency Anonymity for Organizational Networks
Ludovic Barman, Italo Dacosta, Mahdi Zamani +5
Organizational networks are vulnerable to traffic-analysis attacks that enable adversaries to infer sensitive information from the network traffic - even if encryption is used. Typ…
Open, privacy-preserving protocols for lawful surveillance
Aaron Segal, Joan Feigenbaum, Bryan Ford
The question of how government agencies can acquire actionable, useful information about legitimate but unknown targets without intruding upon the electronic activity of innocent p…
Avoiding The Man on the Wire: Improving Tor's Security with Trust-Aware Path Selection
Aaron Johnson, Rob Jansen, Aaron D. Jaggard +2
Tor users are vulnerable to deanonymization by an adversary that can observe some Tor relays or some parts of the network. We demonstrate that previous network-aware path-selection…
Reuse It Or Lose It: More Efficient Secure Computation Through Reuse of Encrypted Values
Benjamin Mood, Debayan Gupta, Kevin Butler +1
Two-party secure function evaluation (SFE) has become significantly more feasible, even on resource-constrained devices, because of advances in server-aided computation systems. Ho…
Representing Network Trust and Using It to Improve Anonymous Communication
Aaron D. Jaggard, Aaron Johnson, Paul Syverson +1
Motivated by the effectiveness of correlation attacks against Tor, the censorship arms race, and observations of malicious relays in Tor, we propose that Tor users capture their tr…