Semantic technologies to support the user-centric analysis of activity data

There is currently a trend in giving access to users of on-line services to their own data. In this paper, we consider in particular the data which is generated from the interaction between a user and an organisation online: activity data as held in websites and Web applications logs. We show how we use semantic technologies including RDF integration of log data, SPARQL and lightweight ontology reasoning to aggregate, integrate and analyse activity data from a user-centric point of view

A System For Visual Role-Based Policy Modelling

The definition of security policies in information systems and programming applications is often accomplished through traditional low level languages that are difficult to use. This is a remarkable drawback if we consider that security policies are often specified and maintained by top level enterprise managers who would probably prefer to use simplified, metaphor oriented policy management tools. To support all the different kinds of users we propose a suite of visual languages to specify access and security policies according to the role based access control (RBAC) model. Moreover, a system implementing the proposed visual languages is proposed. The system provides a set of tools to enable a user to visually edit security policies and to successively translate them into (eXtensible Access Control Markup Language) code, which can be managed by a Policy Based Management System supporting such policy language. The system and the visual approach have been assessed by means of usability studies and of several case studies. The one presented in this paper regards the configuration of access policies for a multimedia content management platform providing video streaming services also accessible through mobile devices

Model-Based Analysis of Role-Based Access Control

Model-Driven Engineering (MDE) has been extensively studied. Many directions have been explored, sometimes with the dream of providing a fully integrated approach for designers, developers and other stakeholders to create, reason about and modify models representing software systems. Most, but not all, of the research in MDE has focused on general-purpose languages and models, such as Java and UML. Domain-specific and cross-cutting concerns, such as security, are increasingly essential parts of a software system, but are only treated as second-class citizens in the most popular modelling languages. Efforts have been made to give security, and in particular access control, a more prominent place in MDE, but most of these approaches require advanced knowledge in security, programming (often declarative), or both, making them difficult to use by less technically trained stakeholders. In this thesis, we propose an approach to modelling, analysing and automatically fixing role-based access control (RBAC) that does not require users to write code or queries themselves. To this end, we use two UML profiles and associated OCL constraints that provide the modelling and analysis features. We propose a taxonomy of OCL constraints and use it to define a partial order between categories of constraints, that we use to propose strategies to speed up the models’ evaluation time. Finally, by representing OCL constraints as constraints on a graph, we propose an automated approach for generating lists of model changes that can be applied to an incorrect model in order to fix it. All these features have been fully integrated into a UML modelling IDE, IBM Rational Software Architect

Model-Based Analysis of Role-Based Access Control

Model-Driven Engineering (MDE) has been extensively studied. Many directions have been explored, sometimes with the dream of providing a fully integrated approach for designers, developers and other stakeholders to create, reason about and modify models representing software systems. Most, but not all, of the research in MDE has focused on general-purpose languages and models, such as Java and UML. Domain-specific and cross-cutting concerns, such as security, are increasingly essential parts of a software system, but are only treated as second-class citizens in the most popular modelling languages. Efforts have been made to give security, and in particular access control, a more prominent place in MDE, but most of these approaches require advanced knowledge in security, programming (often declarative), or both, making them difficult to use by less technically trained stakeholders. In this thesis, we propose an approach to modelling, analysing and automatically fixing role-based access control (RBAC) that does not require users to write code or queries themselves. To this end, we use two UML profiles and associated OCL constraints that provide the modelling and analysis features. We propose a taxonomy of OCL constraints and use it to define a partial order between categories of constraints, that we use to propose strategies to speed up the models’ evaluation time. Finally, by representing OCL constraints as constraints on a graph, we propose an automated approach for generating lists of model changes that can be applied to an incorrect model in order to fix it. All these features have been fully integrated into a UML modelling IDE, IBM Rational Software Architect

Personal Data Stores (PDS): A Review

Internet services have collected our personal data since their inception. In the beginning, the personal data collection was uncoordinated and was limited to a few selected data types such as names, ages, birthdays, etc. Due to the widespread use of social media, more and more personal data has been collected by different online services. We increasingly see that Internet of Things (IoT) devices are also being adopted by consumers, making it possible for companies to capture personal data (including very sensitive data) with much less effort and autonomously at a very low cost. Current systems architectures aim to collect, store, and process our personal data in the cloud with very limited control when it comes to giving back to citizens. However, Personal Data Stores (PDS) have been proposed as an alternative architecture where personal data will be stored within households, giving us complete control (self-sovereignty) over our data. This paper surveys the current literature on Personal Data Stores (PDS) that enable individuals to collect, control, store, and manage their data. In particular, we provide a comprehensive review of related concepts and the expected benefits of PDS platforms. Further, we compare and analyse existing PDS platforms in terms of their capabilities and core components. Subsequently, we summarise the major challenges and issues facing PDS platforms’ development and widespread adoption