Tao Wang (Hong Kong University of Science and Technology)

Tor is an anonymity network that allows clients to browse web pages privately, but loading web pages with Tor is slow. To analyze how the browser loads web pages, we examine their resource trees using our new browser logging and simulation tool, BLAST. We find that the time it takes to load a web page with Tor is almost entirely determined by the number of round trips incurred, not its bandwidth, and Tor Browser incurs unnecessary round trips. Resources sit in the browser queue excessively waiting for the TCP, TLS or ALPN handshakes, each of which takes a separate round trip. We show that increasing resource loading capacity with larger pipelines and even HTTP/2 do not decrease load time because they do not save round trips.

We set out to minimize round trips with a number of protocol and browser improvements, including TCP Fast Open, optimistic data, zero-RTT TLS. We also recommend the use of databases to assist the client with redirection, identifying HTTP/2 servers, and prefetching. All of these features are designed to cut down on the number of round trips incurred in loading web pages. To evaluate these proposed improvements, we create a simulation tool and validate that it is highly accurate in predicting mean page load times. We use the simulator to analyze these features and it predicts that they will decrease the mean page load time by 61% in total over HTTP/2. Our large improvement to user experience comes at trivial cost to the Tor network.

View More Papers

SymTCP: Eluding Stateful Deep Packet Inspection with Automated Discrepancy...

Zhongjie Wang (University of California, Riverside), Shitong Zhu (University of California, Riverside), Yue Cao (University of California, Riverside), Zhiyun Qian (University of California, Riverside), Chengyu Song (University of California, Riverside), Srikanth V. Krishnamurthy (University of California, Riverside), Kevin S. Chan (U.S. Army Research Lab), Tracy D. Braun (U.S. Army Research Lab)

Read More

FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic

Thijs van Ede (University of Twente), Riccardo Bortolameotti (Bitdefender), Andrea Continella (UC Santa Barbara), Jingjing Ren (Northeastern University), Daniel J. Dubois (Northeastern University), Martina Lindorfer (TU Wien), David Choffnes (Northeastern University), Maarten van Steen (University of Twente), Andreas Peter (University of Twente)

Read More

Broken Metre: Attacking Resource Metering in EVM

Daniel Perez (Imperial College London), Benjamin Livshits (Imperial College London, UCL Centre for Blockchain Technologies, and Brave Software)

Read More

TKPERM: Cross-platform Permission Knowledge Transfer to Detect Overprivileged Third-party...

Faysal Hossain Shezan (University of Virginia), Kaiming Cheng (University of Virginia), Zhen Zhang (Johns Hopkins University), Yinzhi Cao (Johns Hopkins University), Yuan Tian (University of Virginia)

Read More