Security and privacy for web databases and services

Abstract. A semantic web can be thought of as a web that is highly intelligent and sophisticated and one needs little or no human intervention to carry out tasks such as scheduling appointments, coordinating activities, searching for complex documents as well as integrating disparate databases and information systems. While much progress has been made toward developing such an intelligent web, there is still a lot to be done. For example, there is little work on security and privacy for the semantic web. However, before we examine security for the semantic web we need to ensure that its key components, such as web databases and services, are secure. This paper will mainly focus on security and privacy issues for web databases and services. Finally, some directions toward developing a secure semantic web will be provided

Bio-grids and applications (QFAB)

Delivering bioinformatics power to life science researchers will inevitably run into the problem of limited computing resources, access time, and costs. Access to grid technology and systems can help to overcome these limitations although this presents its own complexities with problems of security, privacy, storage and integration of disparate data in a potentially confusing environment. QFAB, as the catalyst for interdisciplinary research across biotechnology, health and ICT is developing a suite of tools and skills that will allow its partners to tap into the grid infrastructure of APAC and QCIF. Currently QFAB partners have the opportunity to utilise the power of grid computing via its web services which provide a user friendly environment in which to conduct their work. These web enabled services currently provide integrated access to multiple global genomic, proteomic and chemical databases linked to the ENSEMBL and UCSC genome browser mirrors, modeling software and to de-identified clinical data, providing the researcher with the power to accelerate their discovery and innovation processes

Library application of Deep Web and Dark Web technologies

The Deep Web and Dark Web are legitimate tools for use in the field of information science, adding to the discussion of patron privacy. The American Library Association policies on privacy and confidentiality combined with the advancement of internet technology necessitate that library professionals become fluent in Dark Web usability in libraries

GINSENG (Global Initiative for Sentinel E-health Network on Grid)

The GINSENG (Global Initiative for Sentinel E-health Network on Grid) project aims to implement a grid infrastructure for ehealthand epidemiology in Auvergne. A distributed medical database is created upon a secure network for epidemiologicalstudies. Our goal is to create a decentralized information system using grid technologies. The medical sites involved in theproject are clustered around two themes: cancer monitoring and perinatal care. On each medical site a server whichduplicates the medical database, is deployed with grid services. At the same time, full control of the information is kept by theorganizations storing patients' files. This solution allows for a high level of security, privacy, availability, and fault tolerance.Queries made on the distributed medical databases are made via a secure web portal. Public health authorities use thisinfrastructure for health monitoring, epidemiological studies and evaluation of specific medical practices

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

Privacy in the Genomic Era

Genome sequencing technology has advanced at a rapid pace and it is now possible to generate highly-detailed genotypes inexpensively. The collection and analysis of such data has the potential to support various applications, including personalized medical services. While the benefits of the genomics revolution are trumpeted by the biomedical community, the increased availability of such data has major implications for personal privacy; notably because the genome has certain essential features, which include (but are not limited to) (i) an association with traits and certain diseases, (ii) identification capability (e.g., forensics), and (iii) revelation of family relationships. Moreover, direct-to-consumer DNA testing increases the likelihood that genome data will be made available in less regulated environments, such as the Internet and for-profit companies. The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy. While the computer scientists have addressed data privacy for various data types, there has been less attention dedicated to genomic data. Thus, the goal of this paper is to provide a systematization of knowledge for the computer science community. In doing so, we address some of the (sometimes erroneous) beliefs of this field and we report on a survey we conducted about genome data privacy with biomedical specialists. Then, after characterizing the genome privacy problem, we review the state-of-the-art regarding privacy attacks on genomic data and strategies for mitigating such attacks, as well as contextualizing these attacks from the perspective of medicine and public policy. This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward