Cloud-based Privacy-Preserving Collaborative Consumption for Sharing Economy

Cloud computing has been a dominant paradigm for a variety of information processing platforms, particularly for enabling various popular applications of sharing economy. However, there is a major concern regarding data privacy on these cloud-based platforms. This work presents novel cloud-based privacy-preserving solutions to support collaborative consumption applications for sharing economy. In typical collaborative consumption, information processing platforms need to enable fair cost-sharing among multiple users for utilizing certain shared facilities and communal services. Our cloud-based privacy-preserving protocols, based on homomorphic Paillier cryptosystems, can ensure that the cloud-based operator can only obtain an aggregate schedule of all users in facility sharing, or a service schedule conforming to service provision rule in communal service sharing, but is unable to track the personal schedules or demands of individual users. More importantly, the participating users are still able to settle cost-sharing among themselves in a fair manner for the incurred costs, without knowing each other's private schedules or demands. Our privacy-preserving protocols involve no other third party who may compromise privacy. We also provide an extensive evaluation study and a proof-of-concept system prototype of our protocols.Comment: To appear in IEEE Trans. Cloud Computin

Sensing as a Service Model for Smart Cities Supported by Internet of Things

The world population is growing at a rapid pace. Towns and cities are accommodating half of the world's population thereby creating tremendous pressure on every aspect of urban living. Cities are known to have large concentration of resources and facilities. Such environments attract people from rural areas. However, unprecedented attraction has now become an overwhelming issue for city governance and politics. The enormous pressure towards efficient city management has triggered various Smart City initiatives by both government and private sector businesses to invest in ICT to find sustainable solutions to the growing issues. The Internet of Things (IoT) has also gained significant attention over the past decade. IoT envisions to connect billions of sensors to the Internet and expects to use them for efficient and effective resource management in Smart Cities. Today infrastructure, platforms, and software applications are offered as services using cloud technologies. In this paper, we explore the concept of sensing as a service and how it fits with the Internet of Things. Our objective is to investigate the concept of sensing as a service model in technological, economical, and social perspectives and identify the major open challenges and issues.Comment: Transactions on Emerging Telecommunications Technologies 2014 (Accepted for Publication

Privacy Enhancing Technologies Whitepaper:Developed by Centre of Excellence – Data Sharing and Cloud

This whitepaper provides decision-makers with insights on the benefits of Privacy Enhancing Technologies (PETs) for data collaborations. With recent growth and development of data sharing, public and private organisations can realise new economic and societal value potential. However, data collaboration participants often face barriers for data sharing in form of privacy, commercial and reputational risks. PETs can play a role for reducing these barriers and increasing trust in data collaborations where data cannot be shared directly, since PETs allow to generate insights without disclosing the underlying data. The paper focuses on the most important PETs and their benefits for respective use cases. It also covers challenges that need to be overcome for large-scale adoption of PETs and lastly, shows tangible steps for fostering implementation of these technologies in organisations

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

Cloud technology options towards Free Flow of Data

This whitepaper collects the technology solutions that the projects in the Data Protection, Security and Privacy Cluster propose to address the challenges raised by the working areas of the Free Flow of Data initiative. The document describes the technologies, methodologies, models, and tools researched and developed by the clustered projects mapped to the ten areas of work of the Free Flow of Data initiative. The aim is to facilitate the identification of the state-of-the-art of technology options towards solving the data security and privacy challenges posed by the Free Flow of Data initiative in Europe. The document gives reference to the Cluster, the individual projects and the technologies produced by them