Towards FollowMe User Profiles for Macro Intelligent Environments

We envision an Ambient Intelligent Environment as an environment with technology embedded within the framework of that environment to help enhance an users experience in that environment. Existing implementations , while working effectively, are themselves an expensive and time consuming investment. Applying the same expertise to an environment on a monolithic scale is very inefficient, and thus, will require a different approach. In this paper, we present this problem, propose theoretical solutions that would solve this problem, with the guise of experimentally verifying and comparing these approaches, as well as a formal method to model the entire scenario

My private cloud--granting federated access to cloud resources

We describe the research undertaken in the six month JISC/EPSRC funded My Private Cloud project, in which we built a demonstration cloud file storage service that allows users to login to it, by using their existing credentials from a configured trusted identity provider. Once authenticated, users are shown a set of accounts that they are the owners of, based on their identity attributes. Once users open one of their accounts, they can upload and download files to it. Not only that, but they can then grant access to their file resources to anyone else in the federated system, regardless of whether their chosen delegate has used the cloud service before or not. The system uses standard identity management protocols, attribute based access controls, and a delegation service. A set of APIs have been defined for the authentication, authorisation and delegation processes, and the software has been released as open source to the community. A public demonstration of the system is available online

Link Before You Share: Managing Privacy Policies through Blockchain

With the advent of numerous online content providers, utilities and applications, each with their own specific version of privacy policies and its associated overhead, it is becoming increasingly difficult for concerned users to manage and track the confidential information that they share with the providers. Users consent to providers to gather and share their Personally Identifiable Information (PII). We have developed a novel framework to automatically track details about how a users' PII data is stored, used and shared by the provider. We have integrated our Data Privacy ontology with the properties of blockchain, to develop an automated access control and audit mechanism that enforces users' data privacy policies when sharing their data across third parties. We have also validated this framework by implementing a working system LinkShare. In this paper, we describe our framework on detail along with the LinkShare system. Our approach can be adopted by Big Data users to automatically apply their privacy policy on data operations and track the flow of that data across various stakeholders.Comment: 10 pages, 6 figures, Published in: 4th International Workshop on Privacy and Security of Big Data (PSBD 2017) in conjunction with 2017 IEEE International Conference on Big Data (IEEE BigData 2017) December 14, 2017, Boston, MA, US