Digital Forensics for Eucalyptus

Zafarullah,; Anwar, Faiza; Anwar, Zahid

doi:10.1109/fit.2011.28

Cited by 43 publications

(30 citation statements)

References 6 publications

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“…Zafarullah et al were able to monitor the activity of a Eucalyptus-based cloud and log all internal and external interaction of Eucalyptus components (Zafarullah, 2011). From logs, the were able to track a DDoS attack launched from their Eucalyptus cloud.…”

Section: Related Workmentioning

confidence: 99%

Towards Achieving Reliable Digital Forensics in Iaas and Staas Clouds Using the Open Cloud Forensics Model

Zawoad¹,

Hasan²,

Skjellum³

2016

STCC

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The rapid adoption of cloud computing to meet storage and computation needs has changed the way computing services and resources are used. However, because of the black-box nature and multi-tenant usage models of clouds, existing digital forensics science cannot cope with current state-of-the-art cloud architectures. Because of the fundamental characteristics of such clouds, many assumptions of digital forensics are invalidated. In the digital forensics process involving clouds, the role of cloud service providers (CSPs) is extremely important; a role which needs to be considered in the science of cloud forensics. In this paper, we define cloud forensics while considering the role of the CSP and propose the Open Cloud Forensics (OCF) model. The OCF model focuses on preserving sufficient electronically stored information (ESI) required to investigate cases involving clouds and ensuring the trustworthiness of such ESI. Based on this we propose two cloud architectures: the OCF-supported Infrastructure-asa-Service (IaaS) cloud and the OCF-supported Storage-as-a-Service (StaaS) cloud. We validate our proposed models using a case study, which is inspired from an actual civil lawsuit.

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Section: Related Workmentioning

confidence: 99%

Towards Achieving Reliable Digital Forensics in Iaas and Staas Clouds Using the Open Cloud Forensics Model

Zawoad¹,

Hasan²,

Skjellum³

2016

STCC

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“…Zafarullah et al [51] propose a centralized approach to analyze log files in an IaaS environment, in which the cloud provider is responsible for forensic investigations. Martini and Choo describe an integrated conceptual digital forensic framework for cloud computing [29].…”

Section: Related Workmentioning

confidence: 99%

CloudIDEA: A Malware Defense Architecture for Cloud Data Centers

Fischer

Kittel

Kolosnjaji

et al. 2015

Lecture Notes in Computer Science

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Abstract. Due to the proliferation of cloud computing, cloud-based systems are becoming an increasingly attractive target for malware. In an Infrastructure-as-a-Service (IaaS) cloud, malware located in a customer's virtual machine (VM) affects not only this customer, but may also attack the cloud infrastructure and other co-hosted customers directly. This paper presents CloudIDEA, an architecture that provides a security service for malware defense in cloud environments. It combines lightweight intrusion monitoring with on-demand isolation, evidence collection, and in-depth analysis of VMs on dedicated analysis hosts. A dynamic decision engine makes on-demand decisions on how to handle suspicious events considering cost-efficiency and quality-of-service constraints.

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“…Based on experiments conducted using objects {A,B} and {A,C}, {D,E}, {F,G}, {F,H} the solution converges to different figures when [1,2], [2,3], [2,4], [2,5], [2,6] root interval are used. Table 3 shows the convergence and functional values of the experiments …”

Section: Data Sets For Conducted Experimentsmentioning

confidence: 99%

“…The testing experiments have generated five different scenarios for the objects {A,B} and {A,C}, {D,E}, {F,G}, {F,H} and the test values [1,2], [2,3], [2,4], [2,5] and [2,6] respectively. The authors chose to carry out these separate tests for two main reasons: To find the convergence of the roots that are treated as data objects that move within the cloud and to find the functional object that will help to show how closeness the objects can be during data provenance.…”

Section: Concept Evaluationmentioning

confidence: 99%

“…At the time of writing this paper, still there exist, no acceptable standards for conducting digital forensic investigations in the cloud environment. As a result of these, the cloud has inherited numerous vulnerabilities in the TCP/IP stack and in the web service protocols [3] and seizing the physical device becomes a big challenge because of constantly changing environment. Therefore, in order for data provenance to provide digital forensic investigators with the physical location we consider the scenario below.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method

Kebande¹,

Karie²

2016

IJCA

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The decline in traditional forensics and the emergence of cloud forensics has made it hard for digital forensic investigators to conduct digital investigations due to inadaptability of the cloud to digital forensic processes. Additionally, data that resides in the cloud is normally scattered across constantly changing data centers, hosts and virtual instances are easily destroyed as they are created. On the same note it is not easy to seize physical devices where a particular crime has occurred and locating the origin of an object in the cloud can be a challenge when we do not know where the actual data resides. Data provenance provides a solution whereby one can trace data based on the tag as it keeps changing directions in the cloud. However, if the distance between two particular tagged data is taken into account then the source and destination of an object can be located easily which can then enable digital forensic investigators to locate the physical devices. The problem that this paper is addressing is that, there is no easy way of locating data provenance in the cloud environment without estimating the distance between tagged data that moves in the cloud. Based on this, the authors have proposed a mechanism for locating the provenance of an object using successive bisection method. Similar test have been carried using different intervals in an experiment and the results are very promising.

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Digital Forensics for Eucalyptus

Cited by 43 publications

References 6 publications

Towards Achieving Reliable Digital Forensics in Iaas and Staas Clouds Using the Open Cloud Forensics Model

Towards Achieving Reliable Digital Forensics in Iaas and Staas Clouds Using the Open Cloud Forensics Model

CloudIDEA: A Malware Defense Architecture for Cloud Data Centers

An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method

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