Making GDPR Usable: A Model to Support Usability Evaluations of Privacy

We introduce a new model for evaluating privacy that builds on the criteria proposed by the EuroPriSe certification scheme by adding usability criteria. Our model is visually represented through a cube, called Usable Privacy Cube (or UP Cube), where each of its three axes of variability captures, respectively: rights of the data subjects, privacy principles, and usable privacy criteria. We slightly reorganize the criteria of EuroPriSe to fit with the UP Cube model, i.e., we show how EuroPriSe can be viewed as a combination of only rights and principles, forming the two axes at the basis of our UP Cube. In this way we also want to bring out two perspectives on privacy: that of the data subjects and, respectively, that of the controllers/processors. We define usable privacy criteria based on usability goals that we have extracted from the whole text of the General Data Protection Regulation. The criteria are designed to produce measurements of the level of usability with which the goals are reached. Precisely, we measure effectiveness, efficiency, and satisfaction, considering both the objective and the perceived usability outcomes, producing measures of accuracy and completeness, of resource utilization (e.g., time, effort, financial), and measures resulting from satisfaction scales. In the long run, the UP Cube is meant to be the model behind a new certification methodology capable of evaluating the usability of privacy, to the benefit of common users. For industries, considering also the usability of privacy would allow for greater business differentiation, beyond GDPR compliance.Comment: 41 pages, 2 figures, 1 table, and appendixe

Opportunities for information sharing: case studies

Personal information provided to government and non-government service providers is highly sensitive. Appropriate collection, management and storage of personal information are critical elements to citizen trust in the public sector. However, misconceptions about the frameworks governing sharing personal information can impact on the coordination of services, case management and policy development.   The NSW Department of Premier & Cabinet engaged the Social Policy Research Centre to develop three case studies that identified the challenges to sharing information appropriately, and the opportunities for better personal information sharing between government agencies and non-government organisations. Improved sharing of personal information in these areas can support more effective policy development, leading to improved service delivery performance and coordination.   The Social Policy Research Centre identified the legislative and policy framework for each case study, conducted qualitative research on the interpretation of this framework, and developed three case study reports

Exploring Consumers’ Attitudes of Smart TV Related Privacy Risks

A number of privacy risks are inherent in the Smart TV ecosystem. It is likely that many consumers are unaware of these privacy risks. Alternatively, they might be aware but consider the privacy risks acceptable. In order to explore this, we carried out an online survey with 200 participants to determine whether consumers were aware of Smart TV related privacy risks. The responses revealed a meagre level of awareness. We also explored consumers’ attitudes towards specific Smart TV related privacy risks. We isolated a number of factors that influenced rankings and used these to develop awareness-raising messages. We tested these messages in an online survey with 155 participants. The main finding was that participants were generally unwilling to disconnect their Smart TVs from the Internet because they valued the Smart TV’s Internet functionality more than their privacy. We subsequently evaluated the awareness-raising messages in a second survey with 169 participants, framing the question differently. We asked participants to choose between five different Smart TV Internet connection options, two of which retained functionality but entailed expending time and/or effort to preserve privacy

Control responsibility : the discursive construction of privacy, teens, and Facebook in Flemish newspapers

This study explores the discursive construction of online privacy through a critical discourse analysis of Flemish newspapers' coverage of privacy, teens, and Facebook between 2007 and 2018 to determine what representation of (young) users the papers articulate. A privacy-as-control discourse is dominant and complemented by two other discourses: that of the unconcerned and reckless teenager and that of the promise of media literacy. Combined, these discourses form an authoritative language on privacy that we call "control responsibility." Control responsibility presents privacy as an individual responsibility that can be controlled and needs to be learned by young users. We argue that the discourses contribute to a neoliberal rationality and have a disciplinary effect that strengthens various forms of responsibilization

ConXsense - Automated Context Classification for Context-Aware Access Control

We present ConXsense, the first framework for context-aware access control on mobile devices based on context classification. Previous context-aware access control systems often require users to laboriously specify detailed policies or they rely on pre-defined policies not adequately reflecting the true preferences of users. We present the design and implementation of a context-aware framework that uses a probabilistic approach to overcome these deficiencies. The framework utilizes context sensing and machine learning to automatically classify contexts according to their security and privacy-related properties. We apply the framework to two important smartphone-related use cases: protection against device misuse using a dynamic device lock and protection against sensory malware. We ground our analysis on a sociological survey examining the perceptions and concerns of users related to contextual smartphone security and analyze the effectiveness of our approach with real-world context data. We also demonstrate the integration of our framework with the FlaskDroid architecture for fine-grained access control enforcement on the Android platform.Comment: Recipient of the Best Paper Awar

PRIMA — Privacy research through the perspective of a multidisciplinary mash up

Based on a summary description of privacy protection research within three fields of inquiry, viz. social sciences, legal science, and computer and systems sciences, we discuss multidisciplinary approaches with regard to the difficulties and the risks that they entail as well as their possible advantages. The latter include the identification of relevant perspectives of privacy, increased expressiveness in the formulation of research goals, opportunities for improved research methods, and a boost in the utility of invested research efforts

Semi-autonomous, context-aware, agent using behaviour modelling and reputation systems to authorize data operation in the Internet of Things

In this paper we address the issue of gathering the "informed consent" of an end user in the Internet of Things. We start by evaluating the legal importance and some of the problems linked with this notion of informed consent in the specific context of the Internet of Things. From this assessment we propose an approach based on a semi-autonomous, rule based agent that centralize all authorization decisions on the personal data of a user and that is able to take decision on his behalf. We complete this initial agent by integrating context-awareness, behavior modeling and community based reputation system in the algorithm of the agent. The resulting system is a "smart" application, the "privacy butler" that can handle data operations on behalf of the end-user while keeping the user in control. We finally discuss some of the potential problems and improvements of the system.Comment: This work is currently supported by the BUTLER Project co-financed under the 7th framework program of the European Commission. published in Internet of Things (WF-IoT), 2014 IEEE World Forum, 6-8 March 2014, Seoul, P411-416, DOI: 10.1109/WF-IoT.2014.6803201, INSPEC: 1425565