OCommICISSP 2016 Abstracts

Short Papers
Paper Nr: 1

Big Data, Ethics and Comparative Law: an Interdisciplinary Approach


Denise Amram

Abstract: Since the adoption of the Data Protection Directive in 1995, broad technological changes have taken place. In particular, the ability to collect, store and process personal data has considerably increased in few years. The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. Ethical issues arise since big data capabilities may risk to prevailing innovation purposes on our values. Nowadays, our attitude to reveal patterns and new knowledge from previously unexamined patterns of data is moving faster than our current legal and ethical guidelines can manage. The current European legal framework on data protection in the big data processing includes the Charter of Fundamental Rights (Articles 7 and 8), the Directive 95/46/EC (Data Protection Directive) and the relevant provisions of Directive 2002/58/EC as amended by Directive 2009/136/EC . To comply with the current rules and principles aims at “creating and keeping the trust which any stakeholder needs in order to develop a stable business model” that is based on the processing of big data, which may (or may not) involve personal ones. For example, are users aware of the uses made of their data? The answer is formally affirmative, since they should accept Privacy Policy Terms and Conditions (PPTC) before downloading their apps. However, how many users really read and understand these PPTCs? Do PPTCs respect principles emerging from the supranational legal framework? How Privacy protection can be improved without obstructing technological progress? A new challenge for comparative law is to find innovative legal tools and models to empower users’ privacy protection while using new technologies. The research aims at establishing an interdisciplinary debate, offering an analysis of the main legal issues emerging in the big data economy. In particular, possible solutions to balance the technological need to collect and process big data and users’ rights protection will be investigated in the project.

Paper Nr: 2

Controlling data uitility-privacy for publishing linked open government data


Dalal Al-Azizy

Abstract: Recently, open governments are keen to publish data for transparency and accountability among other goals. Publishing data by releasing enormous amounts of datasets to maximize the data utility for public benefits are trending to achieve the goals of open governments. However, one major challenge is that there are no such measurements or systems to inform that data published from certain datasets would contribute to privacy breaches. The advancement of Linked Data to be deployed and used in publishing open government data and therefore machine understandability of data is also making the problem is more challenging. We propose a study that analyse and manage this challenge. This is by designing a system that is responsible of decision-making for publishing data as linked open government data and protected from deanonymisation risk. The study is interested in the analysis and quantification for the trade-off between data utility and privacy for linked open government data with regards to deanonymisability threat to individuals’ data. We propose building a threat model of the deanonymisability on publishing linked open government data and identifying thresholds. The system then test data before publishing on the Web as Linked Open Government Data by a game theoretic approach that based on these thresholds to assist in making decision. We aim to have this system assisting in maximizing the data utility while preserving privacy.