Koslowski T, Zimmermann C
Towards a Detective Approach to Process-Centered Resilience
In: Security and Trust Management (LNCS 8203), Seiten: 176 - 190, R. Accorsi, S. Ranise (Hrsg.), Springer (Berlin Heidelberg), 2013

Kurzfassung Protection of todayâs interconnected and complex information infrastructures is of high priority. Traditionally, protection means robustness: preventively identify the threats to business processes and propose countermeasures within the context of a risk analysis. This, however, only covers known risks having punctual effects upon the IT infrastructure. In contrast, the notion of resilience, as a refinement of trustworthiness, is getting attention both in academia and within organizations as a denominator to move beyond survival and even prosper in the face of adverse conditions. This paper reports on ongoing work towards the development of PREDEC, a detective framework to realize resilience in the context of business processes. Specifically, it firstly motivates the need for operational resilience and corresponding tool support at the level of processes. Secondly, it sketches the operation and building blocks of PREDEC, which currently employs process mining techniques to analyze process event logs to assess systemsâ resilience. Finally, it describes the intended evaluation steps to be undertaken once PREDEC is completely implemented.

Konferenzbeiträge

2016

Cabinakova J, Zimmermann C, Müller G
An Empirical Analysis of Privacy Dashboard Acceptance: The Google Case
2016 24th European Conference on Information Systems, Istanbul, Turkey, June 12-15, 2016 forthcoming
Zimmermann C
Framework and Requirements for Reconciling Digital Services and Privacy
2016 24th European Conference on Information Systems, Istanbul, Turkey, June 12-15, 2016 forthcoming

Zimmermann C, Accorsi R, Müller G
Privacy Dashboards: Reconciling Data-Driven Business Models and Privacy
2014 Proceedings of the 2014 Ninth International Conference on Availability, Reliability and Security (ARES) , Seiten: 152 - 157

Kurzfassung We argue for the use of Privacy Dashboards as enablers for privacy-enabled data-driven business models. Specifically, while dashboards are succesful instruments in business intelligence tools, their use in privacy protection is far less well-understood. Addressing this problem at the technical level, this paper provides a classification scheme for Privacy Dashboards and elaborates on the current state of the art to draw a research agenda for designing Privacy Dashboards that cater to users' desire of control and businesses' need for data collection and usage.

Zimmermann C, Accorsi R
Transparenz durch Privacy Dashboards: Ein Process Mining Ansatz
2013 Koblenz Lecture Notes in Informatics (LNI) - Proceedings Series of the Gesellschaft für Informatik (GI), Band: P-220, Seiten: 2087 - 2101

Accorsi R, Zimmermann C, Müller G
On Taming the Inference Threat in Social Networks
2012 The 1st International Workshop on Privacy and Data Protection Technology (PDPT). Amsterdam Proceedings of the 1st International Workshop on Privacy and Data Protection Technology (PDPT)