By Matthew Brook, Craig Sharp, Graham Morgan (auth.), Jim Dowling, François Taïani (eds.)
This booklet constitutes the refereed lawsuits of the thirteenth IFIP WG 6.1 overseas convention on disbursed functions and Interoperable platforms, DAIS 2013, held in Florence, Italy, in June 2013, as a part of the eighth foreign Federated convention on allotted Computing concepts, DisCoTec 2013. The 12 revised complete papers and nine brief papers provided have been rigorously reviewed and chosen from forty two submissions. The papers current state of the art examine effects and case experiences within the sector of allotted functions and interoperable structures focussing on cloud computing, replicated garage, and peer-to-peer computing.
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Additional info for Distributed Applications and Interoperable Systems: 13th IFIP WG 6.1 International Conference, DAIS 2013, Held as Part of the 8th International Federated Conference on Distributed Computing Techniques, DisCoTec 2013, Florence, Italy, June 3-5, 2013. Proce
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Springer, Boston (2009) 3. : Cloud computing: The impact on digital forensic investigations. In: Proc. of the 4th Int. Conf. for Internet Technology and Secured Transactions, ICITST (2009) 4. : Technical Challenges of Forensic Investigations in Cloud Computing Environments. In: Workshop on Cryptography and Security in Clouds, pp. 1–6 (2011) 5. : Cloud Computing – Benefits, risks and recommendations for information security. ENISA Technical Report (2009) 6. : PyFlag – an advanced network forensic framework.
10] share same aspects of our approach, as they propose a cloud API for forensics data. However, both publications list this idea together with other high level approaches, without presenting many details. Our forensics model is a more specific approach that also discusses aspects of a real prototype implementation. 3 System Model and Security Assumptions This paper considers an IaaS model in which a cloud provider executes virtual machines on behalf of a cloud client. The client has full control over the software running within the virtual machines.
Furthermore, the business model for the cloud provider and benefits for the cloud client need to be discussed. Regarding the scalability of our approach we note that the observed overhead does not depend on the number of physical machines of the cloud provider. If a cloud client uses a single virtual machine in a large cloud, the previously shown overhead exists only on the physical machine hosting the client VM. Our approach can, however, be used to observe multiple client VMs simultaneously. In this case, a single analysis VM can become a bottleneck.