Measuring I2P Censorship at a Global Scale
July 16, 2019 ยท Declared Dead ยท ๐ FOCI @ USENIX Security Symposium
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Nguyen Phong Hoang, Sadie Doreen, Michalis Polychronakis
arXiv ID
1907.07120
Category
cs.CY: Computers & Society
Cross-listed
cs.NI,
cs.SI
Citations
33
Venue
FOCI @ USENIX Security Symposium
Last Checked
2 months ago
Abstract
The prevalence of Internet censorship has prompted the creation of several measurement platforms for monitoring filtering activities. An important challenge faced by these platforms revolves around the trade-off between depth of measurement and breadth of coverage. In this paper, we present an opportunistic censorship measurement infrastructure built on top of a network of distributed VPN servers run by volunteers, which we used to measure the extent to which the I2P anonymity network is blocked around the world. This infrastructure provides us with not only numerous and geographically diverse vantage points, but also the ability to conduct in-depth measurements across all levels of the network stack. Using this infrastructure, we measured at a global scale the availability of four different I2P services: the official homepage, its mirror site, reseed servers, and active relays in the network. Within a period of one month, we conducted a total of 54K measurements from 1.7K network locations in 164 countries. With different techniques for detecting domain name blocking, network packet injection, and block pages, we discovered I2P censorship in five countries: China, Iran, Oman, Qatar, and Kuwait. Finally, we conclude by discussing potential approaches to circumvent censorship on I2P.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Computers & Society
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Artificial Intelligence: the global landscape of ethics guidelines
R.I.P.
๐ป
Ghosted
The role of artificial intelligence in achieving the Sustainable Development Goals
R.I.P.
๐ป
Ghosted
Green AI
R.I.P.
๐ป
Ghosted
Principles alone cannot guarantee ethical AI
R.I.P.
๐ป
Ghosted
Tackling Climate Change with Machine Learning
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted