40,077 research outputs found

    Calm before the storm: the challenges of cloud computing in digital forensics

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    Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their infrastructure into remote, virtualized environments, often hosted and managed by third parties. This development has significant implications for digital forensic investigators, equipment vendors, law enforcement, as well as corporate compliance and audit departments (among others). Much of digital forensic practice assumes careful control and management of IT assets (particularly data storage) during the conduct of an investigation. This paper summarises the key aspects of cloud computing and analyses how established digital forensic procedures will be invalidated in this new environment. Several new research challenges addressing this changing context are also identified and discussed

    Security and Privacy Issues of Big Data

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    This chapter revises the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by Big Data applications. One of them is privacy. It is a pertinent aspect to be addressed because users share more and more personal data and content through their devices and computers to social networks and public clouds. So, a secure framework to social networks is a very hot topic research. This last topic is addressed in one of the two sections of the current chapter with case studies. In addition, the traditional mechanisms to support security such as firewalls and demilitarized zones are not suitable to be applied in computing systems to support Big Data. SDN is an emergent management solution that could become a convenient mechanism to implement security in Big Data systems, as we show through a second case study at the end of the chapter. This also discusses current relevant work and identifies open issues.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201

    A forensically-enabled IASS cloud computing architecture

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    Current cloud architectures do not support digital forensic investigators, nor comply with today’s digital forensics procedures largely due to the dynamic nature of the cloud. Whilst much research has focused upon identifying the problems that are introduced with a cloud-based system, to date there is a significant lack of research on adapting current digital forensic tools and techniques to a cloud environment. Data acquisition is the first and most important process within digital forensics – to ensure data integrity and admissibility. However, access to data and the control of resources in the cloud is still very much provider-dependent and complicated by the very nature of the multi-tenanted operating environment. Thus, investigators have no option but to rely on cloud providers to acquire evidence, assuming they would be willing or are required to by law. Furthermore, the evidence collected by the Cloud Service Providers (CSPs) is still questionable as there is no way to verify the validity of this evidence and whether evidence has already been lost. This paper proposes a forensic acquisition and analysis model that fundamentally shifts responsibility of the data back to the data owner rather than relying upon a third party. In this manner, organisations are free to undertaken investigations at will requiring no intervention or cooperation from the cloud provider. The model aims to provide a richer and complete set of admissible evidence than what current CSPs are able to provide

    Cloud computing services: taxonomy and comparison

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    Cloud computing is a highly discussed topic in the technical and economic world, and many of the big players of the software industry have entered the development of cloud services. Several companies what to explore the possibilities and benefits of incorporating such cloud computing services in their business, as well as the possibilities to offer own cloud services. However, with the amount of cloud computing services increasing quickly, the need for a taxonomy framework rises. This paper examines the available cloud computing services and identifies and explains their main characteristics. Next, this paper organizes these characteristics and proposes a tree-structured taxonomy. This taxonomy allows quick classifications of the different cloud computing services and makes it easier to compare them. Based on existing taxonomies, this taxonomy provides more detailed characteristics and hierarchies. Additionally, the taxonomy offers a common terminology and baseline information for easy communication. Finally, the taxonomy is explained and verified using existing cloud services as examples

    Information standards to support application and enterprise interoperability for the smart grid

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    Copyright @ 2012 IEEE.Current changes in the European electricity industry are driven by regulatory directives to reduce greenhouse gas emissions, at the same time as replacing aged infrastructure and maintaining energy security. There is a wide acceptance of the requirement for smarter grids to support such changes and accommodate variable injections from renewable energy sources. However the design templates are still emerging to manage the level of information required to meet challenges such as balancing, planning and market dynamics under this new paradigm. While secure and scalable cloud computing architectures may contribute to supporting the informatics challenges of the smart grid, this paper focuses on the essential need for business alignment with standardised information models such as the IEC Common Information Model (CIM), to leverage data value and control system interoperability. In this paper we present details of use cases being considered by National Grid, the GB transmission system operator for information interoperability in pan-network system management and planning.This study is financially supported by the National Grid, UK
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