Dissecting Open Edge Computing Platforms: Ecosystem, Usage, and Security Risks

Yu Bi*,1, Mingshuo Yang*,2, Yong Fang1, Xianghang Mi†,1, Shanqing Guo†,2,3, Shujun Tang4, Haixin Duan4,5
1University of Science and Technology of China, 2Shandong University,
3Shandong Key Laboratory of Artificial Intelligence Security,
4Qi An Xin Technology Research Institute, 5Tsinghua University
ACSAC 2024
*Both authors contributed equally to this research.
†Corresponding authors.
Paper Code arXiv

The Open Edge Computing Ecosystem

Abstract

Emerging in recent years, open edge computing platforms (OECPs) claim large-scale edge nodes, the extensive usage and adoption, as well as the openness to any third parties to join as edge nodes. For instance, OneThingCloud, a major OECP operated in China, advertises 5 million edge nodes, 70TB bandwidth, and 1,500PB storage. However, little information is publicly available for such OECPs with regards to their technical mechanisms and involvement in edge computing activities. Furthermore, different from known edge computing paradigms, OECPs feature an open ecosystem wherein any third party can participate as edge nodes and earn revenue for the contribution of computing and bandwidth resources, which, however, can introduce byzantine or even malicious edge nodes and thus break the traditional threat model for edge computing. In this study, we conduct the first empirical study on two representative OECPs, which is made possible through the deployment of edge nodes across locations, the efficient and semi-automatic analysis of edge traffic as well as the carefully designed security experiments. As the results, a set of novel findings and insights have been distilled with regards to their technical mechanisms, the landscape of edge nodes, the usage and adoption, and the practical security/privacy risks. Particularly, millions of daily active edge nodes have been observed, which feature a wide distribution in the network space and the extensive adoption in content delivery towards end users of 16 popular Internet services. Also, multiple practical and concerning security risks have been identified along with acknowledgements received from relevant parties, e.g., the exposure of long-term and cross-edge-node credentials, the co-location with malicious activities of diverse categories, the failures of TLS certificate verification, the extensive information leakage against end users, etc.

Collecting and Analyzing Edge Activities

To figure out what purpose the OECP traffic flow is intended for, and what remote parties have communicated with our self-deployed edge nodes, and ultimately understand what edge computing activities have been conducted in OECPs, we pursue edge tasks through a combination of manual analysis and automatic measurements.
The manual analysis allows us to gain qualitative knowledge such as the categories of edge traffic flows, and the signatures to associate traffic flows with different categories or distinct remote parties. The automatic measurements are designed to generate quantitative measurement results, e.g., the volume and shares of different traffic categories.

The Pipeline of the Edge Traffic Analyzer

The Ecosystem

The Security Risks

More security risks can be found in our paper.

BibTeX

@article{bi2024dissectingopenedgecomputing,
      title={Dissecting Open Edge Computing Platforms: Ecosystem, Usage, and Security Risks}, 
      author={Yu Bi and Mingshuo Yang and Yong Fang and Xianghang Mi and Shanqing Guo and Shujun Tang and Haixin Duan},
      year={2024},
      eprint={2404.09681},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2404.09681}
}