QUIC Hunter: Finding QUIC Deployments and Identifying Server Libraries Across the Internet

TL;DR

This paper presents a method to detect and identify various QUIC server implementations across the Internet, enhancing measurement accuracy and providing insights into the QUIC ecosystem's diversity.

Contribution

It introduces an improved detection approach for QUIC deployments and a technique to identify server libraries based on connection frames and transport parameters.

Findings

Identified at least one deployment for 18 QUIC libraries.

Detected 8.0 million IPv4 and 2.5 million IPv6 addresses hosting these libraries.

Enhanced detection rate of QUIC implementations through new measurement techniques.

Abstract

The diversity of QUIC implementations poses challenges for Internet measurements and the analysis of the QUIC ecosystem. While all implementations follow the same specification and there is general interoperability, differences in performance, functionality, but also security (e.g., due to bugs) can be expected. Therefore, knowledge about the implementation of an endpoint on the Internet can help researchers, operators, and users to better analyze connections, performance, and security. In this work, we improved the detection rate of QUIC scans to find more deployments and provide an approach to effectively identify QUIC server libraries based on CONNECTION CLOSE frames and transport parameter orders. We performed Internet-wide scans and identified at least one deployment for 18 QUIC libraries. In total, we can identify the libraries with 8.0 M IPv4 and 2.5 M IPv6 addresses. We provide a comprehensive view of the landscape of competing QUIC libraries.