3,947 research outputs found

    Privacy in the Genomic Era

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    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

    Ontology-based Access Control in Open Scenarios: Applications to Social Networks and the Cloud

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    La integració d'Internet a la societat actual ha fet possible compartir fàcilment grans quantitats d'informació electrònica i recursos informàtics (que inclouen maquinari, serveis informàtics, etc.) en entorns distribuïts oberts. Aquests entorns serveixen de plataforma comuna per a usuaris heterogenis (per exemple, empreses, individus, etc.) on es proporciona allotjament d'aplicacions i sistemes d'usuari personalitzades; i on s'ofereix un accés als recursos compartits des de qualsevol lloc i amb menys esforços administratius. El resultat és un entorn que permet a individus i empreses augmentar significativament la seva productivitat. Com ja s'ha dit, l'intercanvi de recursos en entorns oberts proporciona importants avantatges per als diferents usuaris, però, també augmenta significativament les amenaces a la seva privacitat. Les dades electròniques compartides poden ser explotades per tercers (per exemple, entitats conegudes com "Data Brokers"). Més concretament, aquestes organitzacions poden agregar la informació compartida i inferir certes característiques personals sensibles dels usuaris, la qual cosa pot afectar la seva privacitat. Una manera de del.liar aquest problema consisteix a controlar l'accés dels usuaris als recursos potencialment sensibles. En concret, la gestió de control d'accés regula l'accés als recursos compartits d'acord amb les credencials dels usuaris, el tipus de recurs i les preferències de privacitat dels propietaris dels recursos/dades. La gestió eficient de control d'accés és crucial en entorns grans i dinàmics. D'altra banda, per tal de proposar una solució viable i escalable, cal eliminar la gestió manual de regles i restriccions (en la qual, la majoria de les solucions disponibles depenen), atès que aquesta constitueix una pesada càrrega per a usuaris i administradors . Finalment, la gestió del control d'accés ha de ser intuïtiu per als usuaris finals, que en general no tenen grans coneixements tècnics.La integración de Internet en la sociedad actual ha hecho posible compartir fácilmente grandes cantidades de información electrónica y recursos informáticos (que incluyen hardware, servicios informáticos, etc.) en entornos distribuidos abiertos. Estos entornos sirven de plataforma común para usuarios heterogéneos (por ejemplo, empresas, individuos, etc.) donde se proporciona alojamiento de aplicaciones y sistemas de usuario personalizadas; y donde se ofrece un acceso ubicuo y con menos esfuerzos administrativos a los recursos compartidos. El resultado es un entorno que permite a individuos y empresas aumentar significativamente su productividad. Como ya se ha dicho, el intercambio de recursos en entornos abiertos proporciona importantes ventajas para los distintos usuarios, no obstante, también aumenta significativamente las amenazas a su privacidad. Los datos electrónicos compartidos pueden ser explotados por terceros (por ejemplo, entidades conocidas como “Data Brokers”). Más concretamente, estas organizaciones pueden agregar la información compartida e inferir ciertas características personales sensibles de los usuarios, lo cual puede afectar a su privacidad. Una manera de paliar este problema consiste en controlar el acceso de los usuarios a los recursos potencialmente sensibles. En concreto, la gestión de control de acceso regula el acceso a los recursos compartidos de acuerdo con las credenciales de los usuarios, el tipo de recurso y las preferencias de privacidad de los propietarios de los recursos/datos. La gestión eficiente de control de acceso es crucial en entornos grandes y dinámicos. Por otra parte, con el fin de proponer una solución viable y escalable, es necesario eliminar la gestión manual de reglas y restricciones (en la cual, la mayoría de las soluciones disponibles dependen), dado que ésta constituye una pesada carga para usuarios y administradores. Por último, la gestión del control de acceso debe ser intuitivo para los usuarios finales, que por lo general carecen de grandes conocimientos técnicos.Thanks to the advent of the Internet, it is now possible to easily share vast amounts of electronic information and computer resources (which include hardware, computer services, etc.) in open distributed environments. These environments serve as a common platform for heterogeneous users (e.g., corporate, individuals etc.) by hosting customized user applications and systems, providing ubiquitous access to the shared resources and requiring less administrative efforts; as a result, they enable users and companies to increase their productivity. Unfortunately, sharing of resources in open environments has significantly increased the privacy threats to the users. Indeed, shared electronic data may be exploited by third parties, such as Data Brokers, which may aggregate, infer and redistribute (sensitive) personal features, thus potentially impairing the privacy of the individuals. A way to palliate this problem consists on controlling the access of users over the potentially sensitive resources. Specifically, access control management regulates the access to the shared resources according to the credentials of the users, the type of resource and the privacy preferences of the resource/data owners. The efficient management of access control is crucial in large and dynamic environments such as the ones described above. Moreover, in order to propose a feasible and scalable solution, we need to get rid of manual management of rules/constraints (in which most available solutions rely) that constitutes a serious burden for the users and the administrators. Finally, access control management should be intuitive for the end users, who usually lack technical expertise, and they may find access control mechanism more difficult to understand and rigid to apply due to its complex configuration settings

    Data Leak Detection As a Service: Challenges and Solutions

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    We describe a network-based data-leak detection (DLD) technique, the main feature of which is that the detection does not require the data owner to reveal the content of the sensitive data. Instead, only a small amount of specialized digests are needed. Our technique – referred to as the fuzzy fingerprint – can be used to detect accidental data leaks due to human errors or application flaws. The privacy-preserving feature of our algorithms minimizes the exposure of sensitive data and enables the data owner to safely delegate the detection to others.We describe how cloud providers can offer their customers data-leak detection as an add-on service with strong privacy guarantees. We perform extensive experimental evaluation on the privacy, efficiency, accuracy and noise tolerance of our techniques. Our evaluation results under various data-leak scenarios and setups show that our method can support accurate detection with very small number of false alarms, even when the presentation of the data has been transformed. It also indicates that the detection accuracy does not degrade when partial digests are used. We further provide a quantifiable method to measure the privacy guarantee offered by our fuzzy fingerprint framework
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