Detecting Cache-Based Side Channel Attacks in IaaS using Enhanced Algorithm
R. Vanathi1, SP. Chokkalingam2
1R. Vanathi, Research Scholar, Saveetha Institute of Medical and Technical Sciences, Chennai India.
2SP. Chokkalingam, Department of Information Technology, Saveetha Institute of Medical and Technical Sciences, Chennai India.
Manuscript received on 21 September 2019 | Revised Manuscript received on 30 September 2019 | Manuscript Published on 01 October 2019 | PP: 227-235 | Volume-8 Issue-9S4 July 2019 | Retrieval Number: I11360789S419/19©BEIESP | DOI: 10.35940/ijitee.I1136.0789S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Connectivity of the information among people throughout the world is made possible through computers and smart devices connected over the internet. The economic related transactions also happen over the network which needs a secured transaction medium. Therefore, lots of intrusion detection and prevention systems are implemented in order to reduce the impact of the attack. But every year the impact of attack over the shared VMs is being dramatically increased. The economic transactions occur with the help of web applications and they are divided into browser-side and server-side components. One of the major services provided by the cloud environment is Infrastructure-asa-Service in which the virtual machines are used to provide the shared services to the multiple users. Though the VMs are secured by implementing the various security algorithms, one of the attacks, Side-channel attack, uses the leaked information acquired from the implementation of hardware component. Cache-based side channel attack is the serious attack, which tries to steal the sensitive information like credit card details, password, medical related details, etc., by establishing various algorithms like PRIME+PROBE, FLUSH+RELOAD, FLUSH+FLUSH, etc.,. The VM does speculative execution for improving the CPU performance, thus resulting in a scenario which allows the user to access the sensitive data on the cache line. So in this paper the environment is set up with 5 various scenarios with the combinations consisting of attack, no-attack, Full load, Average load and no-load. The Hardware Performance Counters (HPC) is used along with Intel CMT to monitor and distinguish the attacker VM, thus increasing the detection accuracy and reducing the system overhead.
Keywords: VM, HPC, CMT, Spectre, LLC
Scope of the Article: Algorithm Engineering