Data confidentiality is one of the pressing challenges in the ongoing research in Cloud computing. Hosting confidential business data at a Cloud Service Provider (CSP) requires the transfer of control over the data to a semi-trusted external service provider. Existing solutions to protect the data mainly rely on cryptographic techniques. However, these cryptographic techniques add computational overhead, in particular when the data is distributed among multiple CSP servers. This paper proposes a fragmentation technique which efficiently stores the data on CSP servers using the minimum possible amount of encryption. The fragmentation procedure is applied to a relational databases where the tables are treated as independent fragments. This fragmentation and distribution approach reduces the trust expectancies towards the external service providers and thus improves privacy and confidentiality.

Software systems are becoming more complex, interconnected and liable to adopt continuous change and evolution. It’s necessary to develop appropriate methods and techniques to ensure security and privacy of such systems. Research efforts that aim to ensure security and privacy of software systems are distinguished through two main categories: (1) the development of requirements engineering methods, and (2) implementation techniques. Approaches that fall in the first category usually aim to address either security or privacy in an implicit way, with emphasis on the security aspects by developing methods to elicit and analyse security (and privacy) requirements. Works that fall in the latter categories focus specifically on the later stages of the development process irrespective of the organisational context in which the system will be incorporated. This work introduces a model-based process for security and privacy requirements engineering. In particular, the authors’ work includes activities which support to identify and analyse security and privacy requirements for the software system. Their purpose process combines concepts from two well-known requirements engineering methods, Secure Tropos and PriS. A real case study from the EU project E-vote, i.e., an Internet based voting system, is employed to demonstrate the applicability of the approach.

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Cyber-physical Production Systems (CPPS) are one of the technical driving forces behind the transformation of industrial production towards "digital factory of the future" in the context of Industry 4.0. Security is a major concern for such systems as they become more intelligent, interconnected, and coupled with physical devices. For various security activities from security analysis to designing security controls and architecture, a systematic and structured view and presentation of security-related information is required. Based on the draft standard of Reference Architecture Model for Industry 4.0 (RAMI 4.0), we propose a practical approach to establish a security viewpoint in the CPPS reference architecture model. We investigate the feasibility of using an architecture modeling tool to implement the concept and leverage existing work on models of layered architecture. We demonstrate the applicability for security analysis in two example case studies.

Due to a lack of transparency in cloud based services well-defined security levels cannot be assured within current cloud infrastructures. Hence sectors with stringent security requirements hesitate to migrate their services to the cloud. This applies especially when considering services where high security requirements are combined with legal constraints. To tackle this challenge this paper presents an extension to our existing work on assurance methodologies in cloud based environments by investigating how current state of the art monitoring solutions can be used to support assurance throughout the entire infrastructure. A case study is used in which monitoring information representing a set of relevant security properties is being collected. As result, we propose that a combination of existing tools should be used to harmonize existing monitoring artifacts. We describe and evaluate an Evidence Gathering Mechanism (EGM) that provides this harmonization and show how this can support assurance. This can also underpin legal proceedings from an evidence law perspective.

The momentum behind Cloud Computing has revolutionized how ICT services are provided, adopted and delivered. Features such as high scalability, fast provisioning, on demand resource availability makes it an attractive proposition for deploying complex and demanding systems. Clouds are also very suitable for deploying systems with unpredictable load patterns including Critical infrastructure services. Though, the major obstacle in hosting Critical infrastructures is often a lack of assurance. The transparency and flexibility offered by the Cloud, abstracts per definition over e.g. data placement, hardware, service migration. This makes it very hard to assure security properties. We present an investigation of assurance approaches, an analysis of their suitability for Critical Infrastructure Services being deployed in the Cloud and presents our approach.

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Abstract-Data with high security requirements is being processed and stored with increasing frequency in the Cloud. To guarantee that the data is being dealt in a secure manner we investigate the applicability of Assurance methodologies. In a typical Cloud environment the setup of multiple layers and different stakeholders determines security properties of individual components that are used to compose Cloud applications. We present a methodology adapted from Common Criteria for aggregating information reflecting the security properties of individual constituent components of Cloud applications. This aggregated information is used to categorise overall application security in terms of Assurance Levels and to provide a continuous assurance level evaluation. It gives the service owner an overview of the security of his service, without requiring detailed manual analyses of log files.