TrustSketch: Trustworthy Sketch-based Telemetry on Cloud Hosts
Zhuo Cheng, Maria Apostolaki, Zaoxing Liu, Vyas Sekar
摘要
—Cloud providers deploy telemetry tools in software to perform end-host network analytics. Recent efforts show that sketches, a kind of approximate data structure, are a promising basis for software-based telemetry, as they provide high fidelity for many statistics with a low resource footprint. However, an attacker can compromise sketch-based telemetry results via software vulnerabilities. Consequently, they can nullify the use of telemetry; e.g., avoiding attack detection or inducing accounting discrepancies. In this paper, we formally define the requirements for trustworthy sketch-based telemetry and show that prior work cannot meet those due to the sketch’s probabilistic nature and performance requirements. We present the design and implementation T RUST S KETCH , a general framework for trustworthy sketch telemetry that can support a wide spectrum of sketching algorithms. We show that T RUST S KETCH is able to detect a wide range of attacks on sketch-based telemetry in a timely fashion while incurring only minimal overhead.
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引用它的顶会 Paper2
- Zoom2Net: Constrained Network Telemetry ImputationFengchen Gong, Divya Raghunathan, Aarti Gupta, Maria ApostolakiSIGCOMM 2024 · 被引用 11 次
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