A Placement Vulnerability Study in Multi-tenant Public Clouds
release_opgteew3c5eafcxo2oicrbfdpq
by
Venkatanathan Varadarajan, Yinqian Zhang, Thomas Ristenpart and
Michael Swift
2015
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 co-location
attacks. We find that adoption of new technologies (e.g., VPC) makes many prior
attacks, such as cloud cartography, ineffective. We find new ways to reliably
test for co-location across Amazon EC2, Google GCE, and Microsoft Azure. We
also found ways to detect co-location with victim web servers in a multi-tiered
cloud application located behind a load balancer.
We use our new co-residence tests and multiple customer accounts to launch VM
instances under different strategies that seek to maximize the likelihood of
co-residency. We find that it is much easier (10x higher success rate) and
cheaper (up to 114 less) to achieve co-location in these three clouds when
compared to a secure reference placement policy.
In text/plain
format
Archived Files and Locations
application/pdf 511.2 kB
file_wa7rqioutrhm7iy7uygza4xexe
|
arxiv.org (repository) web.archive.org (webarchive) |
1507.03114v1
access all versions, variants, and formats of this works (eg, pre-prints)