Special Session on Industry 4.0

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New directions in mobile, hybrid, and heterogeneous clouds for cyberinfrastructures

With the increasing availability of mobile devices and data generated by end-users, scientific instruments and simulations solving many of our most important scientific and engineering problems require innovative technical solutions. These solutions should provide the whole chain to process data and services from the mobile users to the cloud infrastructure, which must also integrate heterogeneous clouds to provide availability, scalability, and data privacy. This special issue presents the results of particular research works showing advances on mobile, hybrid, and heterogeneous clouds for modern cyberinfrastructures

Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

REMIND: A Framework for the Resilient Design of Automotive Systems

In the past years, great effort has been spent on enhancing the security and safety of vehicular systems. Current advances in information and communication technology have increased the complexity of these systems and lead to extended functionalities towards self-driving and more connectivity. Unfortunately, these advances open the door for diverse and newly emerging attacks that hamper the security and, thus, the safety of vehicular systems. In this paper, we contribute to supporting the design of resilient automotive systems. We review and analyze scientific literature on resilience techniques, fault tolerance, and dependability. As a result, we present the REMIND resilience framework providing techniques for attack detection, mitigation, recovery, and resilience endurance. Moreover, we provide guidelines on how the REMIND framework can be used against common security threats and attacks and further discuss the trade-offs when applying these guidelines

Towards performance evaluation of cloud service providers for cloud data security

© 2016, Elsevier Ltd. All rights reserved. Today's data is sensitive that requires privacy and security both from the cloud service providers (CSP) as well as from users in its all the form of data states: data at rest, while transferring data, enquiring data, and processing the data. Cloud computing has been applied in the health sector, national security services, banking and other business and companies that store confidential data into the cloud as we have seen in recent years. Therefore, information and data security is a crucial issue that needs to be addressed thoroughly in the cloud computing business. This research deals with the performance analysis of recent cloud data security models. This paper proposes cloud data security models based on Business Process Modeling Notations (BPMN) and simulation results can reveal performances issues related to data security as part of any organizations initiative on Business process management (BPM)

CERN openlab Whitepaper on Future IT Challenges in Scientific Research

This whitepaper describes the major IT challenges in scientific research at CERN and several other European and international research laboratories and projects. Each challenge is exemplified through a set of concrete use cases drawn from the requirements of large-scale scientific programs. The paper is based on contributions from many researchers and IT experts of the participating laboratories and also input from the existing CERN openlab industrial sponsors. The views expressed in this document are those of the individual contributors and do not necessarily reflect the view of their organisations and/or affiliates

Secure data storage and retrieval in cloud computing

Nowadays cloud computing has been widely recognised as one of the most inuential information technologies because of its unprecedented advantages. In spite of its widely recognised social and economic benefits, in cloud computing customers lose the direct control of their data and completely rely on the cloud to manage their data and computation, which raises significant security and privacy concerns and is one of the major barriers to the adoption of public cloud by many organisations and individuals. Therefore, it is desirable to apply practical security approaches to address the security risks for the wide adoption of cloud computing

The impacts of cloud computing adoption at Higher Education institutions: a SWOT analysis

The integration of advanced technologies within education has frequently enhanced teaching. In higher education it is not a surprise that using the latest developments in cloud computing improves learning practices and thus ensures they are more interactive, available, and convenient. The ease of integration, collaboration, and sharing of information and knowledge made possibleby cloud computing will be further enhanced if this technical advancement is used wisely and in a foolproof manner. In this paper, a SWOT analysis of the impact of cloud computing on higher education methodologies is presented. A SWOT analysis is here demonstrated to be a helpful guide in decision-making for all higher education institutions when considering the migration of their present learning systems to cloud based systems