Grid infrastructures for secure access to and use of bioinformatics data: experiences from the BRIDGES project

The BRIDGES project was funded by the UK Department of Trade and Industry (DTI) to address the needs of cardiovascular research scientists investigating the genetic causes of hypertension as part of the Wellcome Trust funded (£4.34M) cardiovascular functional genomics (CFG) project. Security was at the heart of the BRIDGES project and an advanced data and compute grid infrastructure incorporating latest grid authorisation technologies was developed and delivered to the scientists. We outline these grid infrastructures and describe the perceived security requirements at the project start including data classifications and how these evolved throughout the lifetime of the project. The uptake and adoption of the project results are also presented along with the challenges that must be overcome to support the secure exchange of life science data sets. We also present how we will use the BRIDGES experiences in future projects at the National e-Science Centre

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

Self-healing Multi-Cloud Application Modelling

Cloud computing market forecasts and technology trends confirm that Cloud is an IT disrupting phenomena and that the number of companies with multi-cloud strategy is continuously growing. Cost optimization and increased competitiveness of companies that exploit multi-cloud will only be possible when they are able to leverage multiple cloud offerings, while mastering both the complexity of multiple cloud provider management and the protection against the higher exposure to attacks that multi-cloud brings. This paper presents the MUSA Security modelling language for multi-cloud applications which is based on the Cloud Application Modelling and Execution Language (CAMEL) to overcome the lack of expressiveness of state-of-the-art modelling languages towards easing: a) the automation of distributed deployment, b) the computation of composite Service Level Agreements (SLAs) that include security and privacy aspects, and c) the risk analysis and service match-making taking into account not only functionality and business aspects of the cloud services, but also security aspects. The paper includes the description of the MUSA Modeller as the Web tool supporting the modelling with the MUSA modelling language. The paper introduces also the MUSA SecDevOps framework in which the MUSA Modeller is integrated and with which the MUSA Modeller will be validated.The MUSA project leading to this paper has received funding from the European Union’s Horizon 2020 research and innovation pro- gramme under grant agreement No 644429

Threats Management Throughout the Software Service Life-Cycle

Software services are inevitably exposed to a fluctuating threat picture. Unfortunately, not all threats can be handled only with preventive measures during design and development, but also require adaptive mitigations at runtime. In this paper we describe an approach where we model composite services and threats together, which allows us to create preventive measures at design-time. At runtime, our specification also allows the service runtime environment (SRE) to receive alerts about active threats that we have not handled, and react to these automatically through adaptation of the composite service. A goal-oriented security requirements modelling tool is used to model business-level threats and analyse how they may impact goals. A process flow modelling tool, utilising Business Process Model and Notation (BPMN) and standard error boundary events, allows us to define how threats should be responded to during service execution on a technical level. Throughout the software life-cycle, we maintain threats in a centralised threat repository. Re-use of these threats extends further into monitoring alerts being distributed through a cloud-based messaging service. To demonstrate our approach in practice, we have developed a proof-of-concept service for the Air Traffic Management (ATM) domain. In addition to the design-time activities, we show how this composite service duly adapts itself when a service component is exposed to a threat at runtime.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

A Graphical Adversarial Risk Analysis Model for Oil and Gas Drilling Cybersecurity

Oil and gas drilling is based, increasingly, on operational technology, whose cybersecurity is complicated by several challenges. We propose a graphical model for cybersecurity risk assessment based on Adversarial Risk Analysis to face those challenges. We also provide an example of the model in the context of an offshore drilling rig. The proposed model provides a more formal and comprehensive analysis of risks, still using the standard business language based on decisions, risks, and value.Comment: In Proceedings GraMSec 2014, arXiv:1404.163