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DCDIDP: A Distributed, Collaborative, and Data-driven IDP Framework for the Cloud

Abstract

Recent advances in distributed computing, grid computing, virtualization mechanisms, and utility computing led into Cloud Computing as one of the industry buzz words of our decade. As the popularity of the services provided in the cloud environment grows exponentially, the exploitation of possible vulnerabilities grows with the same pace. Intrusion Detection and Prevention Systems (IDPSs) are one of the most popular tools among the front line fundamental tools to defend the computation and communication infrastructures from the intruders. In this poster, we propose a distributed, collaborative, and data-driven IDP (DCDIDP) framework for cloud computing environments. Both cloud providers and cloud customers will benefit significantly from DCDIDP that dynamically evolves and gradually mobilizes the resources in the cloud as suspicion about attacks increases. Such system will provide homogeneous IDPS for all the cloud providers that collaborate distributively. It will respond to the attacks, by collaborating with other peers and in a distributed manner, as near as possible to attack sources and at different levels of operations (e.g. network, host, VM). We present the DCDIDP framework and explain its components. However, further explanation is part of our ongoing work

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