Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

The medical science DMZ: a network design pattern for data-intensive medical science

Abstract: Objective We describe a detailed solution for maintaining high-capacity, data-intensive network flows (eg, 10, 40, 100 Gbps+) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods High-end networking, packet-filter firewalls, network intrusion-detection systems. Results We describe a “Medical Science DMZ” concept as an option for secure, high-volume transport of large, sensitive datasets between research institutions over national research networks, and give 3 detailed descriptions of implemented Medical Science DMZs. Discussion The exponentially increasing amounts of “omics” data, high-quality imaging, and other rapidly growing clinical datasets have resulted in the rise of biomedical research “Big Data.” The storage, analysis, and network resources required to process these data and integrate them into patient diagnoses and treatments have grown to scales that strain the capabilities of academic health centers. Some data are not generated locally and cannot be sustained locally, and shared data repositories such as those provided by the National Library of Medicine, the National Cancer Institute, and international partners such as the European Bioinformatics Institute are rapidly growing. The ability to store and compute using these data must therefore be addressed by a combination of local, national, and industry resources that exchange large datasets. Maintaining data-intensive flows that comply with the Health Insurance Portability and Accountability Act (HIPAA) and other regulations presents a new challenge for biomedical research. We describe a strategy that marries performance and security by borrowing from and redefining the concept of a Science DMZ, a framework that is used in physical sciences and engineering research to manage high-capacity data flows. Conclusion By implementing a Medical Science DMZ architecture, biomedical researchers can leverage the scale provided by high-performance computer and cloud storage facilities and national high-speed research networks while preserving privacy and meeting regulatory requirements

Guest Editorial: Special Issue on Frontiers in Trust Management

Information and Communication Technologies (ICT) are becoming increasingly important in the way we organize our lives, our workplaces and our societies. ICT allows people and organisations, that have never interacted with each other in the past, to initiate new and mutually beneficial businesses across the world. This means that personal and business information is increasingly being communicated across interpersonal, inter-business and international borders. Keeping this information safe and protecting the fragile IT infrastructure from criminals is a growing problem in most societies. Unfortunately, traditional security technologies based on a strong perimeter defence work poorly in an inter-connected world that obeys Metcalfe’s law which states that “the value of a network is proportional to the square of the number of connected users of the system”, i.e., where there is a strong incentive for interactions across the different borders. During the past decade, trust management has emerged as a promising solution to many challenges in networks and distributed systems as well as emerging problems in computer security and privacy. This special issue on “Frontiers in Trust Management” attempts to highlight some of the latest re- search addressing those challenges. It collects a series of papers on trust management issues that extends papers and ideas presented at the Fifth IFIP WG 11.11 International Conference on Trust Management or one of the affiliated workshops in Copenhagen, June 27 – July 1, 2011

Security and privacy issues in cloud computing

International audienceCloud computing is a state-of-the-art technological innovation providing an extensive list of benefits for almost every business and governmental, small or medium-sized organizations. It has truly revolutionized the computational era by cutting down cost and reducing complexities of infrastructural configurations for computational platforms. This state-of-the-art technology is rapidly being adapted by various large organizations from healthcare to critical infrastructure to carry out their business processes that, otherwise, would require large storage capacity, huge computational power, and expensive hardware. The purpose of this special issue was to arrange a venue for cloud researchers around the world to share their state-of-the-art research and development that could benefit the cloud community. This helped collect high-quality articles that reported recent research advances regarding security and privacy issues in cloud computing, covering various topics of interest

How can SMEs benefit from big data? Challenges and a path forward

Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft