Towards assessing information privacy in microblogging online social networks. The IPAM framework

Les xarxes socials en línia incorporen diferents formes de comunicació interactiva com serveis de microblogs, compartició de fitxers multimèdia o xarxes de contactes professionals. En els últims anys han augmentat els escàndols públics en relació amb pràctiques qüestionables de la indústria de les xarxes socials pel que fa a la privacitat. Així, doncs, cal una avaluació efectiva i eficient del nivell de privacitat en les xarxes socials en línia. El focus de la present tesi és la construcció d'un esquema (IPAM) per a identificar i avaluar el nivell de privacitat proporcionat per les xarxes socials en línia, en particular per als serveis de microblogs. L'objectiu d'IPAM és ajudar els usuaris a identificar els riscos relacionats amb les seves dades. L'esquema també permet comparar el nivell de protecció de la privacitat entre diferents sistemes analitzats, de manera que pugui ser també utilitzat per proveïdors de servei i desenvolupadors per a provar i avaluar els seus sistemes i si les tècniques de privacitat usades són eficaces i suficients.Las redes sociales en línea incorporan diferentes formas de comunicación interactiva como servicios de microblogueo, compartición de ficheros multimedia o redes de contactos profesionales. En los últimos años han aumentado los escándalos públicos relacionados con prácticas cuestionables de la industria de las redes sociales en relación con la privacidad. Así pues, es necesaria una evaluación efectiva y eficiente del nivel de privacidad en las redes sociales en línea. El foco de la presente tesis es la construcción de un esquema (IPAM) para identificar y evaluar el nivel de privacidad proporcionado por las redes sociales en línea, en particular para los servicios de microblogueo. El objetivo de IPAM es ayudar a los usuarios a identificar los riesgos relacionados con sus datos. El esquema también permite comparar el nivel de protección de la privacidad entre diferentes sistemas analizados, de modo que pueda ser también utilizado por proveedores de servicio y desarrolladores para probar y evaluar sus sistemas y si las técnicas de privacidad usadas son eficaces y suficientes.Online social networks (OSNs) incorporate different forms of interactive communication, including microblogging services, multimedia sharing and business networking, among others. In recent years there has been an increase in the number of privacy-related public scandals involving questionable data handling practices in OSNs. This situation calls for an effective and efficient evaluation of the privacy level provided by such services. In this thesis, we take initial steps towards developing an information privacy assessment framework (IPAM framework) to compute privacy scores for online social networks in general, and microblogging OSNs in particular. The aim of the proposed framework is to help users identify personal data-related risks and how their privacy is protected when using one OSN or another. The IPAM framework also allows for a comparison between different systems' privacy protection level. This gives system providers, not only an idea of how they are positioned in the market vis-à-vis their competitors, but also recommendations on how to enhance their services

Big Data Processing Attribute Based Access Control Security

The purpose of this research is to analyze the security of next-generation big data processing (BDP) and examine the feasibility of applying advanced security features to meet the needs of modern multi-tenant, multi-level data analysis. The research methodology was to survey of the status of security mechanisms in BDP systems and identify areas that require further improvement. Access control (AC) security services were identified as priority area, specifically Attribute Based Access Control (ABAC). The exemplar BDP system analyzed is the Apache Hadoop ecosystem. We created data generation software, analysis programs, and posted the detailed the experiment configuration on GitHub. Overall, our research indicates that before a BDP system, such as Hadoop, can be used in operational environment significant security configurations are required. We believe that the tools are available to achieve a secure system, with ABAC, using Apache Ranger and Apache Atlas. However, these systems are immature and require verification by an independent third party. We identified the following specific actions for overall improvement: consistent provisioning of security services through a data analyst workstation, a common backplane of security services, and a management console. These areas are partially satisfied in the current Hadoop ecosystem, continued AC improvements through the open source community, and rigorous independent testing should further address remaining security challenges. Robust security will enable further use of distributed, cluster BDP, such as Apache Hadoop and Hadoop-like systems, to meet future government and business requirements

IEEE Transactions on Dependable and Secure Computing An Access Control Model for Online Social Networks Using User-to-User Relationships

Abstract-Users and resources in online social networks (OSNs) are interconnected via various types of relationships. In particular, user-to-user relationships form the basis of the OSN structure, and play a significant role in specifying and enforcing access control. Individual users and the OSN provider should be enabled to specify which access can be granted in terms of existing relationships. In this paper, we propose a novel user-to-user relationship-based access control (UURAC) model for OSN systems that utilizes regular expression notation for such policy specification. Access control policies on users and resources are composed in terms of requested action, multiple relationship types, the starting point of the evaluation, and the number of hops on the path. We present two path checking algorithms to determine whether the required relationship path between users for a given access request exists. We validate the feasibility of our approach by implementing a prototype system and evaluating the performance of these two algorithms