NetVigil: Robust and Low-Cost Anomaly Detection for East-West Data Center Security

Authors: 

Kevin Hsieh, Microsoft; Mike Wong, Princeton University and Microsoft; Santiago Segarra, Microsoft and Rice University; Sathiya Kumaran Mani, Trevor Eberl, and Anatoliy Panasyuk, Microsoft; Ravi Netravali, Princeton University; Ranveer Chandra and Srikanth Kandula, Microsoft

Abstract: 

The growing number of breaches in data centers underscores an urgent need for more effective security. Traditional perimeter defense measures and static zero-trust approaches are unable to address the unique challenges that arise from the scale, complexity, and evolving nature of today's data center networks. To tackle these issues, we introduce NetVigil, a robust and cost-efficient anomaly detection system specifically designed for east-west traffic within data center networks. NetVigil adeptly extracts security-focused, graph-based features from network flow logs and employs domain-specific graph neural networks (GNNs) and contrastive learning techniques to strengthen its resilience against normal traffic variations and adversarial evasion strategies. Our evaluation, over various attack scenarios and traces from real-world production clusters, shows that NetVigil delivers significant improvements in accuracy, cost, and detection latency compared to state-of-the-art anomaly detection systems, providing a practical, supplementary security mechanism to protect the east-west traffic within data center networks.

NSDI '24 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

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BibTeX
@inproceedings {295687,
author = {Kevin Hsieh and Mike Wong and Santiago Segarra and Sathiya Kumaran Mani and Trevor Eberl and Anatoliy Panasyuk and Ravi Netravali and Ranveer Chandra and Srikanth Kandula},
title = {{NetVigil}: Robust and {Low-Cost} Anomaly Detection for {East-West} Data Center Security},
booktitle = {21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24)},
year = {2024},
isbn = {978-1-939133-39-7},
address = {Santa Clara, CA},
pages = {1771--1789},
url = {https://www.usenix.org/conference/nsdi24/presentation/hsieh},
publisher = {USENIX Association},
month = apr
}

Presentation Video