Co-location Detection on the Cloud

被引：12

作者：

Inci, Mehmet Sinan ^{[1
]}

Gulmezoglu, Berk ^{[1
]}

Eisenbarth, Thomas ^{[1
]}

Sunar, Berk ^{[1
]}

机构：

[1] Worcester Polytech Inst, Worcester, MA 01609 USA

来源：

CONSTRUCTIVE SIDE-CHANNEL ANALYSIS AND SECURE DESIGN, COSADE 2016 | 2016年 / 9689卷

基金：

美国国家科学基金会;

关键词：

Co-location on the cloud; Software profiling; Cache covert channel; Performance degradation attacks; Memory bus locking;

D O I：

10.1007/978-3-319-43283-0_2

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this work we focus on the problem of co-location as a first step of conducting Cross-VM attacks such as Prime and Probe or Flush+Reload in commercial clouds. We demonstrate and compare three co-location detection methods namely, cooperative Last-Level Cache (LLC) covert channel, software profiling on the LLC and memory bus locking. We conduct our experiments on three commercial clouds, Amazon EC2, Google Compute Engine and Microsoft Azure. Finally, we show that both cooperative and non-cooperative co-location to specific targets on cloud is still possible on major cloud services.

引用

页码：19 / 34

页数：16

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