Quantitative Analysis of Opacity in Cloud Computing Systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Federated cloud systems increase the reliability and reduce the cost of the computational support. The resulting combination of secure private clouds and less secure public clouds, together with the fact that resources need to be located within different clouds, strongly affects the information flow security of the entire system. In this paper, the clouds as well as entities of a federated cloud system are assigned security levels, and a probabilistic flow sensitive security model for a federated cloud system is proposed. Then the notion of opacity --- a notion capturing the security of information flow --- of a cloud computing systems is introduced, and different variants of quantitative analysis of opacity are presented. As a result, one can track the information flow in a cloud system, and analyze the impact of different resource allocation strategies by quantifying the corresponding opacity characteristics

SciTokens: Capability-Based Secure Access to Remote Scientific Data

The management of security credentials (e.g., passwords, secret keys) for computational science workflows is a burden for scientists and information security officers. Problems with credentials (e.g., expiration, privilege mismatch) cause workflows to fail to fetch needed input data or store valuable scientific results, distracting scientists from their research by requiring them to diagnose the problems, re-run their computations, and wait longer for their results. In this paper, we introduce SciTokens, open source software to help scientists manage their security credentials more reliably and securely. We describe the SciTokens system architecture, design, and implementation addressing use cases from the Laser Interferometer Gravitational-Wave Observatory (LIGO) Scientific Collaboration and the Large Synoptic Survey Telescope (LSST) projects. We also present our integration with widely-used software that supports distributed scientific computing, including HTCondor, CVMFS, and XrootD. SciTokens uses IETF-standard OAuth tokens for capability-based secure access to remote scientific data. The access tokens convey the specific authorizations needed by the workflows, rather than general-purpose authentication impersonation credentials, to address the risks of scientific workflows running on distributed infrastructure including NSF resources (e.g., LIGO Data Grid, Open Science Grid, XSEDE) and public clouds (e.g., Amazon Web Services, Google Cloud, Microsoft Azure). By improving the interoperability and security of scientific workflows, SciTokens 1) enables use of distributed computing for scientific domains that require greater data protection and 2) enables use of more widely distributed computing resources by reducing the risk of credential abuse on remote systems.Comment: 8 pages, 6 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

B2B Infrastructures in the Process of Drug Discovery and Healthcare

In this paper we describe a demonstration of an innovative B2B infrastructure which can be used to support collaborations in the pharmaceutical industry to achieve the drug discovery goal. Based on experience gained in a wide range of collaborative projects in the areas of grid technology, semantics and data management we show future work and new topics in B2B infrastructures which arise when considering the use of patient records in the process of drug discovery and in healthcare applications

A generic framework for process execution and secure multi-party transaction authorization

Process execution engines are not only an integral part of workflow and business process management systems but are increasingly used to build process-driven applications. In other words, they are potentially used in all kinds of software across all application domains. However, contemporary process engines and workflow systems are unsuitable for use in such diverse application scenarios for several reasons. The main shortcomings can be observed in the areas of interoperability, versatility, and programmability. Therefore, this thesis makes a step away from domain specific, monolithic workflow engines towards generic and versatile process runtime frameworks, which enable integration of process technology into all kinds of software. To achieve this, the idea and corresponding architecture of a generic and embeddable process virtual machine (ePVM), which supports defining process flows along the theoretical foundation of communicating extended finite state machines, are presented. The architecture focuses on the core process functionality such as control flow and state management, monitoring, persistence, and communication, while using JavaScript as a process definition language. This approach leads to a very generic yet easily programmable process framework. A fully functional prototype implementation of the proposed framework is provided along with multiple example applications. Despite the fact that business processes are increasingly automated and controlled by information systems, humans are still involved, directly or indirectly, in many of them. Thus, for process flows involving sensitive transactions, a highly secure authorization scheme supporting asynchronous multi-party transaction authorization must be available within process management systems. Therefore, along with the ePVM framework, this thesis presents a novel approach for secure remote multi-party transaction authentication - the zone trusted information channel (ZTIC). The ZTIC approach uniquely combines multiple desirable properties such as the highest level of security, ease-of-use, mobility, remote administration, and smooth integration with existing infrastructures into one device and method. Extensively evaluating both, the ePVM framework and the ZTIC, this thesis shows that ePVM in combination with the ZTIC approach represents a unique and very powerful framework for building workflow systems and process-driven applications including support for secure multi-party transaction authorization