Abstract: Healthcare Information Systems typically fall into the group of systems in which the need of data sharing conflicts with the privacy. A myriad of these systems have to, however, constantly communicate among each other. One of the ways to address the dilemma between data sharing and privacy is to use data obfuscation by lowering data accuracy to guarantee patient’s privacy while retaining its usefulness. Even though many obfuscation methods are able to handle numerical values, the obfuscation of non-numerical values (e.g., textual information) is not as trivial, yet extremely important to preserve data utility along the process. In this paper, we preliminary investigate how to exploit ontologies to create obfuscation mechanism for releasing personal and electronic health records (PHR and EHR) to selected audiences with different degrees of obfuscation. Data minimisation and access control should be supported to enforce different actors, e.g., doctors, nurses and managers, will get access to no more information than needed for their tasks. Besides that, ontology-based obfuscation can also be used for the particular case of data anonymisation. In such case, the obfuscation has to comply with a specific criteria to provide anonymity, so that the data set could be safely released. This research contributes to: state the problems in the area; review related privacy and data protection legal requirements; discuss ontology-based obfuscation and anonymisation methods; and define relevant healthcare use cases. As a result, we present the early concept of our Ontology-based Data Sharing Service (O-DSS) that enforces patient’s privacy by means of obfuscation and anonymisation functions.

Citation: Iwaya, Leonardo H. and Giunchiglia, Fausto and Martucci, Leonardo A. and Hume, Alethia and Fischer-H{\”u}bner, Simone and Chenu-Abente, Ronald, “Ontology-Based Obfuscation and Anonymisation for Privacy”, In “Privacy and Identity Management. Time for a Revolution? 10th IFIP WG 9.2, 9.5, 9.6/11.7, 11.4, 11.6/SIG 9.2.2 International Summer School, Edinburgh, UK, August 16-21, 2015, Revised Selected Papers”, 2016, Springer International Publishing, Cham, pages 343–358, isbn 978-3-319-41763-9, doi 10.1007/978-3-319-41763-9_23, http://dx.doi.org/10.1007/978-3-319-41763-9_23. New York, USA, July 2016.

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Abstract: Collective adaptive systems (CASs) have been researched intensively since many years. However, the recent emerging developments and advanced models in service-oriented computing, cloud computing and human computation have fostered several new forms of CASs. Among them, Hybrid and Diversity-aware CASs (HDA-CASs) characterize new types of CASs in which a collective is composed of hybrid machines and humans that collaborate together with different complementary roles. This emerging HDA-CAS poses several research challenges in terms of programming, management and provisioning. In this paper, we investigate the main issues in programming HDA-CASs. First, we analyze context characterizing HDA-CASs. Second, we propose to use the concept of hybrid compute units to implement HDA-CASs that can be elastic. We call this type of HDA-CASs h2h2 CAS (Hybrid Compute Unit-based HDA-CAS). We then discuss a meta-view of h2h2 CAS that describes a h2h2 CAS program. We analyze and present program features for h2h2 CAS in four main different contexts.

Citation: Hong-Linh Truong, Schahram Dustdar, “Context-aware Programming for Hybrid and Diversity-aware Collective Adaptive Systems”, Springer, International Workshop on Business Processes in Collective Adaptive Systems (BPCAS 2014), 12th Intl. Conf. on Business Process Management (BPM14), Eindhoven, The Netherlands, September 7-12, 2014

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Abstract: This chapter is concerned with how social order is established within collectives and the ethical problems that arise when we attempt to create and direct collectives towards particular ends. It draws on our work to establish governance principles for Smart Society—an EU project aiming to engineer Collective Adaptive Systems comprised of people and machines with diverse capabilities and goals that are able to tackle societal grand challenges. We examine how social values are implicated in and transformed by Collective Adaptive Systems, and suggest approaches to multilevel governance design that are responsive to emergent capabilities and sensitive to conflicting perspectives. Finally we illustrate our approach with a worked example of a sensor-based system in a care setting.

Citation: Hartswood, M., Grimpe, B., and Jirotka, M., “Towards the ethical governance of Smart Society”, In Miorandi, D., Maltese, V., Rovatsos, M., Nijholt., A. and Stewart, J. (eds) Social collective intelligence: Combining the powers of humans and machines Springer, 2014.

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Abstract: The impact of Social Collective Intelligent Systems (SCIS) on the individual right of privacy is discussed in this chapter under the light of the relevant privacy principles of the European Data Protection Legal Framework and the OECD Privacy Guidelines. This chapter analyzes the impact and limits of profiling, provenance and reputation on the right of privacy and review the legal privacy protection for profiles. From the technical perspective, we discuss opportunities and challenges for designing privacy-preserving systems for SCIS concerning collectives and decentralized systems. Furthermore, we present a selection of privacy-enhancing technologies that are relevant for SCIS including anonymous credentials, transparency-enhancing tools and the PrimeLife Policy Language (PPL) and discuss how these technologies can help to enforce the main legal principles of the European Data Protection Legal Framework.

Citation: Fischer-Hübner, S. and Martucci, L. A., “Privacy in Social Collective Intelligence Systems”, in Miorandi, D., Maltese, V., Rovatsos, M., Nijholt., A. and Stewart, J. (eds) Social collective intelligence: Combining the powers of humans and machines Springer, 2014.

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Citation: Miorandi, D., Maltese, V., Rovatsos, M., Nijholt, A., Stewart, J., Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society, Springer, 2014.

Url: http://www.springer.com/gb/book/9783319086804