Covertness Analysis of Snowflake Proxy Request
Yibo Xie, Gaopeng Gou, Gang Xiong, Zhen Li, Mingxin Cui · 2023
Snowflake is a special proxy system against IP-based network blocking. As its IP addresses refresh frequently, faster than IP blacklist’s update, users can exploit it to access blocked websites. To block snowflake, existing methods focus on detecting snowflake proxies. But they are susceptible to various factors, for example, proxy’s location and version. In the paper, we propose a new manner to block snowflake. We observe that to adapt fast IP changes, users need to request latest proxies from proxy database before using snowflake. Thus, adversaries can block snowflake by detecting proxy request instead of proxy itself. To verify our method, we analyse covertness of snowflake proxy requests, that has been protected by imitating normal web requests. After comparing with typical web requests, we find the imitation is vulnerable in packet size, direction, time and network speed, such as, the latency time is higher than normal obviously. Using the four vulnerabilities, we train machine learning algorithm to detect snowflake proxy requests in reality. Experimental results demonstrate that proxy request can be detected accurately across different versions at the beginning of connection. In conclusion, our work paves a new way to block snowflake.