Towards Targeted Intrusion Detection Deployments in Cloud Computing

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Published Jul 1, 2015
https://doi.org/10.47164/ijngc.v6i2.82
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Volume 6, Issue 2, July 2015

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Norman Ahmed
Purdue University
Bharat Bhargava
Purdue University

Abstract

Preventing security violation incidents or collecting dependable system audit trails for post incidents requires successfully detecting anomaly-based abnormal or intrusion activities. However, properly positioning the necessary tools for maximum detection can be inelegant and limited for systems that can be formed and destroyed on demand, such as the cloud. In this paper, we present a simplified taxonomy to aid targeted intrusion detection system deployments in cloud platforms. To illustrate the effectiveness of the proposed approach, we show two stealthy intrusion schemes and a preventive and adoptable detection strategy using Virtual Machine Introspection in a realistic use case scenario.

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How to Cite
Norman Ahmed, & Bharat Bhargava. (2015). Towards Targeted Intrusion Detection Deployments in Cloud Computing. International Journal of Next-Generation Computing, 6(2), 129–139. https://doi.org/10.47164/ijngc.v6i2.82
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