Adaptive detection technique for Cache-based Side Channel Attack using Bloom Filter for secure cloud

Abstract

Security is the one of the main concern in the field of cloud computing. Different users sharing the same physical machines or even software on frequent basis make cloud vulnerable to many security threats. Side channel attacks are the most probable attacks in cloud because of physical resource sharing. In cloud, where multiple Virtual Machines (VM) share same physical machine creates a great opportunity to carry out Cache-based Side Channel Attack (CSCA). In this paper, a novel detection technique using Bloom Filter (BF) for CSCA is designed. This technique treats cache miss sequence as a signature of CSCA and uses a difference mean calculator to generate these signatures. This technique is adaptive, which makes it possible to detect the CSCA with new patterns, which are not observed yet. Bloom filter is used in this technique to reduce the performance overhead to minimum level. The solution is implemented with a cache simulator and proved very effective as it has very less execution time in comparison to the execution time of CSCA.