A Placement Vulnerability Study in Multi-tenant Public Clouds
Venkatanathan Varadarajan, Yinqian Zhang, Thomas Ristenpart and, Michael Swift

TL;DR
This study examines placement vulnerabilities in multi-tenant public clouds, revealing new co-location detection methods and demonstrating increased success rates and cost savings for attackers despite stronger isolation technologies.
Contribution
It introduces novel techniques for testing VM co-location in modern clouds and evaluates how recent security measures impact placement attack effectiveness.
Findings
New co-residence tests for cloud environments
Higher success rates in achieving VM co-location
Cost reduction in placement attack strategies
Abstract
Public infrastructure-as-a-service clouds, such as Amazon EC2, Google Compute Engine (GCE) and Microsoft Azure allow clients to run virtual machines (VMs) on shared physical infrastructure. This practice of multi-tenancy brings economies of scale, but also introduces the risk of sharing a physical server with an arbitrary and potentially malicious VM. Past works have demonstrated how to place a VM alongside a target victim (co-location) in early-generation clouds and how to extract secret information via side- channels. Although there have been numerous works on side-channel attacks, there have been no studies on placement vulnerabilities in public clouds since the adoption of stronger isolation technologies such as Virtual Private Clouds (VPCs). We investigate this problem of placement vulnerabilities and quantitatively evaluate three popular public clouds for their susceptibility to…
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Taxonomy
TopicsSecurity and Verification in Computing · Network Security and Intrusion Detection · Cloud Data Security Solutions
