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Cloud forensics challenges from a service model standpoint: IaaS, PaaS and SaaS

Published:25 October 2015Publication History

ABSTRACT

Cloud computing is a promising and expanding technology which could replace traditional IT systems. Cloud computing resembles a giant pool of resources which contains hardware, software and related applications, which can be accessed through web-based services on a pay-per-usage model. The main features of the cloud model are accessibility, availability and scalability, and it can be subdivided into three service models: Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Cloud computing continues to transform how security challenges are addressed in closed and private networks. Given the advanced functionality offered by cloud computing, network monitoring and digital forensics efforts are potentially detectable and service-interruptive, which significantly impacts the effectiveness and thoroughness of digital forensic methods. This paper presents a general view of cloud computing, which aims to highlight the security issues and vulnerabilities associated with cloud service models. The technology is mainly based on virtualization, where data is always volatile and typically stored in a de-centralized architecture located across various countries and regions. This presents forensics investigators with legal challenges, due to the nature of multi-tenancy and distributed shared resources. This paper examines the three cloud service models and discusses the security challenges and issues involved with each service model along with potential solutions for each.

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  • Published in

    cover image ACM Other conferences
    MEDES '15: Proceedings of the 7th International Conference on Management of computational and collective intElligence in Digital EcoSystems
    October 2015
    271 pages

    Copyright © 2015 ACM

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    Publication History

    • Published: 25 October 2015

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    MEDES '15 Paper Acceptance Rate13of64submissions,20%Overall Acceptance Rate267of682submissions,39%

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