Model-driven Elasticity and DoS Attack Mitigation in Cloud Environments.

ICAC(2014)

Cited 25|Views49
No score
Abstract
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.
More
Translated text
Key words
dos attack mitigation,elasticity,model-driven
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined