https://ris.utwente.nl/ws/files/25251884/privacy_paradox.pdf

The privacy paradox Investigating discrepancies between expressed privacy concerns and actual online behavior A systematic literature review

In this paper we define the notion of a privacy design strategy. These strategies help IT architects to support privacy by design early in the software development life cycle, during concept development and analysis. Using current data protection legislation as point of departure we derive the following eight privacy design strategies: minimise, hide, separate, aggregate, inform, control, enforce, and demonstrate. The strategies also provide a useful classification of privacy design patterns and the underlying privacy enhancing technologies. We therefore believe that these privacy design strategies are not only useful when designing privacy friendly systems, but also helpful when evaluating the privacy impact of existing IT systems.

/pdf/privacy-design-strategies-1sd4fa547b.pdf

Privacy Design Strategies

Privacy and data protection constitute core values of individuals and of democratic societies. There have been decades of debate on how those values -and legal obligations- can be embedded into systems, preferably from the very beginning of the design process. One important element in this endeavour are technical mechanisms, known as privacy-enhancing technologies (PETs). Their effectiveness has been demonstrated by researchers and in pilot implementations. However, apart from a few exceptions, e.g., encryption became widely used, PETs have not become a standard and widely used component in system design. Furthermore, for unfolding their full benefit for privacy and data protection, PETs need to be rooted in a data governance strategy to be applied in practice. This report contributes to bridging the gap between the legal framework and the available technological implementation measures by providing an inventory of existing approaches, privacy design strategies, and technical building blocks of various degrees of maturity from research and development. Starting from the privacy principles of the legislation, important elements are presented as a first step towards a design process for privacy-friendly systems and services. The report sketches a method to map legal obligations to design strategies, which allow the system designer to select appropriate techniques for implementing the identified privacy requirements. Furthermore, the report reflects limitations of the approach. It concludes with recommendations on how to overcome and mitigate these limits.

Privacy and Data Protection by Design - from policy to engineering

Privacy and data protection constitute core values of individuals and of democratic societies. There have been decades of debate on how those values -and legal obligations- can be embedded into systems, preferably from the very beginning of the design process. 
One important element in this endeavour are technical mechanisms, known as privacy-enhancing technologies (PETs). Their effectiveness has been demonstrated by researchers and in pilot implementations. However, apart from a few exceptions, e.g., encryption became widely used, PETs have not become a standard and widely used component in system design. Furthermore, for unfolding their full benefit for privacy and data protection, PETs need to be rooted in a data governance strategy to be applied in practice. 
This report contributes to bridging the gap between the legal framework and the available technological implementation measures by providing an inventory of existing approaches, privacy design strategies, and technical building blocks of various degrees of maturity from research and development. Starting from the privacy principles of the legislation, important elements are presented as a first step towards a design process for privacy-friendly systems and services. The report sketches a method to map legal obligations to design strategies, which allow the system designer to select appropriate techniques for implementing the identified privacy requirements. Furthermore, the report reflects limitations of the approach. It concludes with recommendations on how to overcome and mitigate these limits.

IoT-aided robotics applications

Patterns are a useful approach to describe, organ ize and present solutions and best practices for design problems. Although much work can be found concerning either patterns or privacy, work focusing on patterns for Privacy E nhancing Technologies (PET) is very rare. This paper describ es the development of User Interfaces Patterns for PET and the benefit of using them. We used different proven app roaches and guidelines and merged them for creating efficient and useable patterns for PETs. Anyhow, some of our patterns were not tested much with end-users, so further tests wi ll be necessary to prove worth of the patterns. Neverthel ess we maintain that our patterns will support the develop ment of PET UIs. In this paper, we provide a short overview of the whole pattern collection and present two patterns i n detail.

/pdf/a-pattern-collection-for-privacy-enhancing-technology-1n6vh6osnl.pdf

A Pattern Collection for Privacy Enhancing Technology

In this paper we present uTRUSTit, a project with the goal to increase the users’ understanding of trust in Internet of Things. The Internet of Things consists of complex technology that is often hard to understand for users. Most security properties are hidden in small devices and are not visible for users.Thus, uTRUSTit will display the underlying security implications to the users in order to create a justified level of trust in the Internet of Things.

uTRUSTit – Usable Trust in the Internet of Things

In this deliverable, we present lessons learnt from the PrimeLife HCI (Human Computer Interaction) Activity by discussing typical HCI challenges and fallacies that we experienced during the PrimeLi ...

/pdf/towards-usable-privacy-enhancing-technologies-lessons-fto5bub2zi.pdf

Towards Usable Privacy Enhancing Technologies : Lessons Learned from the PrimeLife Project

This deliverable provides an overview of recent res earch results of Activity 4 ‘Usability’ of PrimeLif e, where an emphasis is put on those results, which ha ve not been reported in the same detail in other HCI-related PrimeLife deliverables yet. The first part reports about our results in the are a of User Interface (UI) Representation of Privacyenhancing Identity Management Concepts and presents research on PET methodologies, mental models for anonymous credentials and the results fr om the final round of end-user evaluations of the U I prototypes developed during the PrimeLife project. The second part reports about our work in the area of usable privacy policies and presents the final r esults of Activity 4’s research on policy icons and on a user -friendly management and display of PPL (PrimeLife Policy Language) policies.

Final HCI Research Report

User-centered design (UCD) processes need to be further extended to the field of privacy enhancing technologies (PETs). The goal of the UCD process for PETs is to provide a means for users to empower them to manage their privacy on the Web. Taking care of privacy and being careful while surfing theWeb are still considered to be cumbersome and time-consuming activities. Hence, PrimeLife aspires to provide easy to use tools for users to manage their privacy. This chapter describes the challenges in UCD that arose during the development of the PrimeLife prototypes. As part of the HCI activities in the PrimeLife project, we have researched the users’ attitudes towards privacy and discovered the main challenges when developing userfriendly PETs. We use two example prototypes to explain how the challenges can be tackled in practice. In general, PETs should neither require much of the user’s attention and time, nor should they require particular technical knowledge. They should, in fact, present the complex methods of privacy enhancing technologies in an easy, understandable and usable way. We will conclude this chapter with a discussion of our findings and implications for further development of user-centered privacy enhancing technologies.

HCI for PrimeLife Prototypes

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