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

SODA: A Generic Online Detection Framework for Smart Contracts

Ting Chen (University of Electronic Science and Technology of China), Rong Cao (University of Electronic Science and Technology of China), Ting Li (University of Electronic Science and Technology of China), Xiapu Luo (The Hong Kong Polytechnic University), Guofei Gu (Texas A&M University), Yufei Zhang (University of Electronic Science and Technology of China), Zhou Liao (University…

Read More

CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples

Honggang Yu (University of Florida), Kaichen Yang (University of Florida), Teng Zhang (University of Central Florida), Yun-Yun Tsai (National Tsing Hua University), Tsung-Yi Ho (National Tsing Hua University), Yier Jin (University of Florida)

Read More

Practical Traffic Analysis Attacks on Secure Messaging Applications

Alireza Bahramali (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst), Ramin Soltani (University of Massachusetts Amherst), Dennis Goeckel (University of Massachusetts Amherst), Don Towsley (University of Massachusetts Amherst)

Read More

Are You Going to Answer That? Measuring User Responses...

Imani N. Sherman (University of Florida), Jasmine D. Bowers (University of Florida), Keith McNamara Jr. (University of Florida), Juan E. Gilbert (University of Florida), Jaime Ruiz (University of Florida), Patrick Traynor (University of Florida)

Read More