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Access control and data separation metrics in cloud infrastructures

: Jaeger, B.; Kraft, R.; Luhn, S.; Selzer, A.; Waldmann, U.


Institute of Electrical and Electronics Engineers -IEEE-:
11th International Conference on Availability, Reliability and Security, ARES 2016 : Salzburg, Austria, 31 August - 2 September 2016; Proceedings
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2016
ISBN: 978-1-5090-0990-9
ISBN: 978-1-5090-0989-3
ISBN: 978-1-5090-0991-6
International Conference on Availability, Reliability and Security (ARES) <11, 2016, Salzburg>
Conference Paper
Fraunhofer SIT ()

An automatically controlled and analyzed privacy level in cloud environments would probably help to allay or at least reduce privacy concerns of prospective clients, in particular if the clients themselves can check the compliance with a required privacy level during regular data processing. However, for each intended control firstly an appropriate set of data sources has to be determined carefully, then the results have to be combined to useful metrics, so that the measurements results approximate specific privacy objectives. This paper proposes appropriate data sources and a partly automatic approach to collect measurement data for controls of separate data processing and access control for clients of cloud infrastructure services (IaaS).