6 research outputs found

    Privacy-preserving data analytics as an outsourced service

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    A MORPHOLOGY OF THE ORGANISATION OF DATA GOVERNANCE

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    Both information systems (IS) researchers and practitioners consider data governance as a promising approach for companies to improve and maintain the quality of corporate data, which is seen as critical for being able to meet strategic business requirements, such as compliance or integrated customer management. Both sides agree that data governance primarily is a matter of organisation. However, hardly any scientific results have been produced so far indicating what actually has to be organised by data governance, and what data governance may look like. The paper aims at closing this gap by developing a morphology of data governance organisation on the basis of a comprehensive analysis of the state of the art both in science and in practice. Epistemologically, the morphology represents an analytic theory, as it serves for structuring the research topic of data governance, which is still quite unexplored. Six mini case studies are used to evaluate the morphology by means of empirical data. Providing a foundation for further research, the morphology contributes to the advancement of the scientific body of knowledge. At the same time, it is beneficial to practitioners, as companies may use it as a guideline when organising data governance

    Confidential database-as-a-service approaches: taxonomy and survey

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    Outsourcing data to external providers has gained momentum with the advent of cloud computing. Encryption allows data confidentiality to be preserved when outsourcing data to untrusted external providers that may be compromised by attackers. However, encryption has to be applied in a way that still allows the external provider to evaluate queries received from the client. Even though confidential database-as-a-service (DaaS) is still an active field of research, various techniques already address this problem, which we call confidentiality preserving indexing approaches (CPIs). CPIs make individual tradeoffs between the functionality provided, i.e., the types of queries that can be evaluated, the level of protection achieved, and performance.In this paper, we present a taxonomy of requirements that CPIs have to satisfy in deployment scenarios including the required functionality and the required level of protection against various attackers. We show that the taxonomy?s underlying principles serve as a methodology to assess CPIs, primarily by linking attacker models to CPI security properties. By use of this methodology, we survey and assess ten previously proposed CPIs. The resulting CPI catalog can help the reader who would like to build DaaS solutions to facilitate DaaS design decisions while the proposed taxonomy and methodology can also be applied to assess upcoming CPI approaches

    Tunable Security for Deployable Data Outsourcing

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    Security mechanisms like encryption negatively affect other software quality characteristics like efficiency. To cope with such trade-offs, it is preferable to build approaches that allow to tune the trade-offs after the implementation and design phase. This book introduces a methodology that can be used to build such tunable approaches. The book shows how the proposed methodology can be applied in the domains of database outsourcing, identity management, and credential management

    A Privacy-Preserving Benchmarking Platform

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    A privacy-preserving benchmarking platform is practically feasible, i.e. its performance is tolerable to the user on current hardware while fulfilling functional and security requirements. This dissertation designs, architects, and evaluates an implementation of such a platform. It contributes a novel (secure computation) benchmarking protocol, a novel method for computing peer groups, and a realistic evaluation of the first ever privacy-preserving benchmarking platform

    Confidential Data-Outsourcing and Self-Optimizing P2P-Networks: Coping with the Challenges of Multi-Party Systems

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    This work addresses the inherent lack of control and trust in Multi-Party Systems at the examples of the Database-as-a-Service (DaaS) scenario and public Distributed Hash Tables (DHTs). In the DaaS field, it is shown how confidential information in a database can be protected while still allowing the external storage provider to process incoming queries. For public DHTs, it is shown how these highly dynamic systems can be managed by facilitating monitoring, simulation, and self-adaptation
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