Lune

INFOCOM2026顶会

CloudPathFI: Uncovering Cross-Layer Vulnerabilities in Cloud Networks via Path-Aware Fault Injection

Yinqin Zhao, Gaoxu Guo, Chang Liu, Long Wang

2026年份

摘要

Cloud networks are critical to modern services, but failures in these networks still happen frequently and are hard to diagnose. To improve reliability, we need to understand which parts of a network are most likely to fail and how different types of faults affect end-to-end communication. Fault injection (FI) is a useful way to study cloud network failures, but current FI tools focus on a single VM/container, APIs, or applications, and cannot test faults along the full network path from source to destination. To address this limitation, we propose CloudPathFI, a fault injection tool that takes actual network paths as input and orchestrates targeted fault injection campaigns along these paths. It supports 15 common fault types based on real cloud incident reports and can test faults across control, data, management, and physical layers. We evaluated CloudPathFI in 924 fault injection experiments, and the results show that CloudPathFI achieves full path coverage, far exceeding baseline tools (6%-60%), while maintaining high reliability (99.78% FI success rate) and low overhead (avg. 4.3% CPU), and uncovering several key findings, such as the fragility of virtual-physical boundaries.

问问这篇 Paper

问问你的智能体。

Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。

可以从这些问题问起

智能体调用

Lunesearch_papers

在 Lune 里问

免费开始,无需绑卡

lune papers get bd6a463e-059d-4301-a430-2284df3cdae6

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖