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Model-driven Elasticity and DoS Attack Mitigation in Cloud Environments
Cornel Barna and Mark Shtern, York University; Michael Smit, Dalhousie University; Hamoun Ghanbari and Marin Litoiu, York University
Workloads for web applications can change rapidly. When the change is an increase in customers, a common adaptive approach to maintain SLAs is elasticity, the on-demand allocation of computing resources. However, application-level denial-of-service (DoS) attacks can also cause changes in workload, and require an entirely different response. These two issues are often addressed separately (in both research and application). This paper presents a model-driven adaptive management mechanism which can correctly scale a web application, mitigate a DoS attack, or both, based on an assessment of the business value of workload. This approach is enabled by modifying a layered queuing network model previously used to model data centers to also accurately predict short-term cloud behavior, despite cloud variability over time. We evaluate our approach on Amazon EC2 and demonstrate the ability to horizontally scale a sample web application in response to an increase in legitimate traffic while mitigating multiple DoS attacks, achieving the established performance goal.
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author = {Cornel Barna and Mark Shtern and Mike Smit and Hamoun Ghanbari and Marin Litoiu},
title = {Model-driven Elasticity and {DoS} Attack Mitigation in Cloud Environments},
booktitle = {11th International Conference on Autonomic Computing (ICAC 14)},
year = {2014},
isbn = {978-1-931971-11-9},
address = {Philadelphia, PA},
pages = {13--24},
url = {https://www.usenix.org/conference/icac14/technical-sessions/presentation/barna},
publisher = {USENIX Association},
month = jun
}
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