An Abstract Model for Integrated Intrusion Detection and Severity Analysis for Clouds

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Author(s): Junaid Arshad (University of Leeds, UK), Paul Townend (University of Leeds, UK) and Jie Xu (University of Leeds, UK)
Copyright: 2011
Volume: 1
Issue: 1
Pages: 16
Source title: International Journal of Cloud Applications and Computing (IJCAC)
Editor(s)-in-Chief: Shadi Aljawarneh (Isra University, Jordan) and Hong Cai (IBM China Software Development Lab, China)
DOI: 10.4018/ijcac.2011010101
ISSN: 2156-1834
EISSN: 2156-1826

Keywords: Business Technologies / Electronic Services / High Performance Computing / Information Science Reference

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Abstract

Cloud computing is an emerging computing paradigm which introduces novel opportunities to establish large scale, flexible computing infrastructures. However, security underpins extensive adoption of Cloud computing. This paper presents efforts to address one of the significant issues with respect to security of Clouds i.e. intrusion detection and severity analysis. An abstract model for integrated intrusion detection and severity analysis for Clouds is proposed to facilitate minimal intrusion response time while preserving the overall security of the Cloud infrastructures. In order to assess the effectiveness of the proposed model, detailed architectural evaluation using Architectural Trade-off Analysis Model (ATAM) is used. A set of recommendations which can be used as a set of best practice guidelines while implementing the proposed architecture is discussed.

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