Detecting Compute Cloud Co-residency with Network Flow Watermarking Techniques
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This paper presents co-resident watermarking, a traffic analysis attack for cloud environments that allows a malicious co-resident virtual machine to inject a watermark signature into the network flow of a target instance. This watermark can be used to exfiltrate co-residency data, compromising isolation assurances. While previous work depends on virtual hypervisor resource management, our approach is difficult to defend without costly underutilization of the physical machine. We evaluate co-resident watermarking under many configurations, from a local lab environment to production cloud environments. We demonstrate the ability to initiate a covert channel of 4 bits per second, and we can confirm co-residency with a target VM instance in less than 10 seconds. We also show that passive load measurement of the target and behavior profiling is possible. Our investigation demonstrates the need for the careful design of hardware to be used in the cloud. This thesis includes unpublished co-authored material.