39,151 research outputs found
Malware Detection in Cloud Computing Infrastructures
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 TermsâSecurity, resilience, invasive software, multi-agent systems, network-level security and protection
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Current capabilities, requirements and a proposed strategy for interdependency analysis in the UK
The UK government recently commissioned a research study to identify the state-of-the-art in Critical Infrastructure modelling and analysis, and the government/industry requirements for such tools and services. This study (Cetifs) concluded with a strategy aiming to bridge the gaps between the capabilities and requirements, which would establish interdependency analysis as a commercially viable service in the near future. This paper presents the findings of this study that was carried out by CSR, City University London, Adelard LLP, a safety/security consultancy and Cranfield University, defense academy of the UK
Multi-Layer Cyber-Physical Security and Resilience for Smart Grid
The smart grid is a large-scale complex system that integrates communication
technologies with the physical layer operation of the energy systems. Security
and resilience mechanisms by design are important to provide guarantee
operations for the system. This chapter provides a layered perspective of the
smart grid security and discusses game and decision theory as a tool to model
the interactions among system components and the interaction between attackers
and the system. We discuss game-theoretic applications and challenges in the
design of cross-layer robust and resilient controller, secure network routing
protocol at the data communication and networking layers, and the challenges of
the information security at the management layer of the grid. The chapter will
discuss the future directions of using game-theoretic tools in addressing
multi-layer security issues in the smart grid.Comment: 16 page
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