A Decision Support System for Design for Privacy

Abstract

Privacy is receiving increased attention from both consumers, who are concerned about how they are being tracked and profiled, and regulators, who are introducing stronger penalties and encouragements for organizations to comply with legislation and to carry out Privacy Impact Assessments (PIAs). These concerns are strengthened as usage of internet services, cloud computing and social networking spread. Therefore companies have to take privacy requirements into account just as they previously had to do this for security. While security mechanisms are relatively mature, system and product developers are not often provided with concrete suggestions from a privacy angle. This can be a problem because developers do not usually possess privacy expertise. In this paper we argue that it would be useful to move beyond current best practice -where a set of searchable privacy guidelines may be provided to developers -to automated support to software developers in early phases of software development. Specifically, our proposal is a decision support system for design for privacy focused on privacy by policy, to be integrated into the development environment. We have implemented a proof of concept and are extending this work to incorporate state-of-the art consent mechanisms derived from the EnCoRe (Ensuring Consent and Revocation) project [1].

Privacy Engineering for Domestic IoT: Enabling Due Diligence

“…Hafiz [26], for example, presents a set of privacy mitigations in response to known attacks and extends the work to present a pattern language to help developers choose patterns that are relevant to a particular domain (for which the domestic IoT is not one) [27]. Pearson [28,29] argue that we need to move beyond guides and checklists and towards “automated support for software developers in early phases of software development” given that “developers do not usually possess privacy expertise”. The authors utilise a decision support-based system where developers provide a set of requirements (in the form of a questionnaire) and these are then used to generate a candidate set of high-level privacy patterns (such as opt-in consent, or negotiation around privacy preferences) that must be implemented by the developer.…”

A Refinement Approach for the Reuse of Privacy Risk Analysis Results

“…Our work is therefore complementary to the above proposals and contributes to establish links between privacy risk analysis and privacy by design. The need to take into account the actual privacy risks or threats is mentioned in a number of papers [25], [34], [38] but, to our best knowledge, has not been explored in detail in previous works.…”

Trust Driven Strategies for Privacy by Design

“…Design patterns are used in [14] to define eight privacy strategies 8 called respectively: Minimise, Hide, Separate, Aggregate, Inform, Control, Enforce and Demonstrate. Other authors put forward pattern-based approaches: [13] proposes a language for privacy patterns allowing for a designer to choose relevant PETs; [29] describes a solution for online interactions; at a higher level, [25] proposes a decision support tool based on design patterns to help software engineers to take into account privacy guidelines in the early stage of development.…”