Knowing Your Population: Privacy-Sensitive Mining of Massive Data

Location and mobility patterns of individuals are important to environmental planning, societal resilience, public health, and a host of commercial applications. Mining telecommunication traffic and transactions data for such purposes is controversial, in particular raising issues of privacy. However, our hypothesis is that privacy-sensitive uses are possible and often beneficial enough to warrant considerable research and development efforts. Our work contends that peoples behavior can yield patterns of both significant commercial, and research, value. For such purposes, methods and algorithms for mining telecommunication data to extract commonly used routes and locations, articulated through time-geographical constructs, are described in a case study within the area of transportation planning and analysis. From the outset, these were designed to balance the privacy of subscribers and the added value of mobility patterns derived from their mobile communication traffic and transactions data. Our work directly contrasts the current, commonly held notion that value can only be added to services by directly monitoring the behavior of individuals, such as in current attempts at location-based services. We position our work within relevant legal frameworks for privacy and data protection, and show that our methods comply with such requirements and also follow best-practice

Designing Data Spaces

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty

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

Dynamic trust negotiation for decentralised e-health collaborations

In the Internet-age, the geographical boundaries that have previously impinged upon inter-organisational collaborations have become decreasingly important. Of more importance for such collaborations is the notion and subsequent nature of security and trust - this is especially so in open collaborative environments like the Grid where resources can be both made available, subsequently accessed and used by remote users from a multitude of institutions with a variety of different privileges spanning across the collaboration. In this context, the ability to dynamically negotiate and subsequently enforce security policies driven by various levels of inter-organisational trust is essential. Numerous access control solutions exist today to address aspects of inter-organisational security. These include the use of centralised access control lists where all collaborating partners negotiate and agree on privileges required to access shared resources. Other solutions involve delegating aspects of access right management to trusted remote individuals in assigning privileges to their (remote) users. These solutions typically entail negotiations and delegations which are constrained by organisations, people and the static rules they impose. Such constraints often result in a lack of flexibility in what has been agreed; difficulties in reaching agreement, or once established, in subsequently maintaining these agreements. Furthermore, these solutions often reduce the autonomous capacity of collaborating organisations because of the need to satisfy collaborating partners demands. This can result in increased security risks or reducing the granularity of security policies. Underpinning this is the issue of trust. Specifically trust realisation between organisations, between individuals, and/or between entities or systems that are present in multi-domain authorities. Trust negotiation is one approach that allows and supports trust realisation. The thesis introduces a novel model called dynamic trust negotiation (DTN) that supports n-tier negotiation hops for trust realisation in multi-domain collaborative environments with specific focus on e-Health environments. DTN describes how trust pathways can be discovered and subsequently how remote security credentials can be mapped to local security credentials through trust contracts, thereby bridging the gap that makes decentralised security policies difficult to define and enforce. Furthermore, DTN shows how n-tier negotiation hops can limit the disclosure of access control policies and how semantic issues that exist with security attributes in decentralised environments can be reduced. The thesis presents the results from the application of DTN to various clinical trials and the implementation of DTN to Virtual Organisation for Trials of Epidemiological Studies (VOTES). The thesis concludes that DTN can address the issue of realising and establishing trust between systems or agents within the e-Health domain, such as the clinical trials domain