Assessing the impact of intra-cloud live migration on anomaly detection

Shirazi, Syed Noorulhassan; Simpson, Steven; Marnerides, Angelos K.; Watson, Michael R.; Mauthe, Andreas; Hutchison, David

doi:10.1109/cloudnet.2014.6968968

Cited by 29 publications

(23 citation statements)

References 11 publications

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“…The method is embodied by a resilience architecture that was initially defined in [4], further explored in [36], [37] and which comprises the System Analysis Engine (SAE) and Network Analysis Engine (NAE) components. These exist as submodules of the architecture's Cloud Resilience Managers (CRMs), which perform detection at the end-system, and in the network respectively.…”

Section: Discussionmentioning

confidence: 99%

Malware Detection in Cloud Computing Infrastructures

2018

IJRTER

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Abstract-Cloud services are prominent within the private, public and commercial domains. Many of these services are expected to be always on and have a critical nature; therefore, security and resilience are increasingly important aspects. In order to remain resilient, a cloud needs to possess the ability to react not only to known threats, but also to new challenges that target cloud infrastructures. In this paper we introduce and discuss an online cloud anomaly detection approach, comprising dedicated detection components of our cloud resilience architecture. More specifically, we exhibit the applicability of novelty detection under the one-class support Vector Machine (SVM) formulation at the hypervisor level, through the utilisation of features gathered at the system and network levels of a cloud node. We demonstrate that our scheme can reach a high detection accuracy of over 90% whilst detecting various types of malware and DoS attacks. Furthermore, we evaluate the merits of considering not only system-level data, but also network-level data depending on the attack type. Finally, the paper shows that our approach to detection using dedicated monitoring components per VM is particularly applicable to cloud scenarios and leads to a flexible detection system capable of detecting new malware strains with no prior knowledge of their functionality or their underlying instructions.Index Terms-Security, resilience, invasive software, multi-agent systems, network-level security and protection.

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Section: Discussionmentioning

confidence: 99%

Malware Detection in Cloud Computing Infrastructures

2018

IJRTER

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“…The method is embodied by a resilience architecture that was initially defined in (Simpson et al, 2013) and further explored in (Shirazi et al, 2014) and (Shirazi et al, 2015).…”

Section: Monitoring Solutionmentioning

confidence: 99%

Towards Resilience Metrics for Future Cloud Applications

Novak

Shirazi

Hudic

et al. 2016

Proceedings of the 6th International Conference on Cloud Computing and Services Science

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Abstract:An analysis of new technologies can yield insight into the way these technologies will be used. Inevitably, new technologies and their uses are likely to result in new security issues regarding threats, vulnerabilities and attack vectors. In this paper, we investigate and analyse technological and security trends and their potential to become future threats by systematically examining industry reports on existing technologies. Using a cloud computing use case we identify potential resilience metrics that can shed light on the security properties of the system.

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“…However, there is still need to apply basic of policy refinement principals for autonomic management in cloud computing. The motivation for the work presented here comes from the previous work [8], [9] and objectives of the project SECCRIT 1 which state:…”

Section: Fig 1: Policy Refinement Stagesmentioning

confidence: 99%

Towards policy refinement for resilience management in cloud

Shirazi

Simpson

Syeda

et al. 2016

2016 8th International Workshop on Resilient Networks Design and Modeling (RNDM)

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Abstract-Cloud computing is becoming increasingly important for provision of critical services because of potential cost saving, scalability and elasticity. Therefore, it is particularly important for clouds and cloud-based services to be resilient, i.e., they are able to operate correctly and continuously even in the presence of challenges. To do this, a number of resiliencesupporting mechanisms are needed at various levels in cloud infrastructure. It is non-trivial to manage these mechanisms and there is a need for flexible instruments which assist cloud providers in this complex task. Policy based management is an established instrument to manage resilience supporting mechanisms and they are useful if it allows not only high level description of abstract policy (e.g high level security and resilience requirements), but also enables such policy to be refined and eventually mapped into an appropriate low levels in cloud settings. This paper sheds light on basic concepts behind policy based management in cloud, more specifically it emphasizes the use of policy refinement which is the process of translating higher level requirements (such as security and resilience requirements) into the sequence of actions at lower levels that can implement them, in order to generate more refined policies that govern the behaviour of an overall cloud system when under challenge. We finally present two example scenarios on how policy refinement can work for the cloud to establish its relevance for the overall resilience management.

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Assessing the impact of intra-cloud live migration on anomaly detection

Cited by 29 publications

References 11 publications

Malware Detection in Cloud Computing Infrastructures

Malware Detection in Cloud Computing Infrastructures

Towards Resilience Metrics for Future Cloud Applications

Towards policy refinement for resilience management in cloud

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