Alexandre Pujol, Christina Thorpe
IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC 2015).
Outsourcing to the Cloud is becoming an attractive option for many organisations dealing with large amounts of data. However, there is still a reluctance amongst companies dealing with highly regulated data because traditional Cloud storage does not support the level of privacy required to prevent access pattern leakage. Oblivious Random Access Machines (ORAM) have been a hot topic of research over the past number of years, proposing various cryptographic techniques to obtain the privacy levels required. We propose a new model, Dog ORAM — a distributed and shared oblivious RAM model with server side computation, that merges several models existing in the literature and includes a new method of access right management for multi-party data access. To achieve this, we use an additive homomorphic encryption scheme and a chameleon signature.Author version Presentation
Alexandre Pujol, Christina Thorpe, Liam Murphy
16th European Conference on Cyber Warfare and Security (ECCWS 2017)
In this work in progress paper, we worked on metadata leakage in the specific use case of an instant messaging server. In a first time, we define the different type of metadata that can be found, then in a second time, we provide a proof of concept using live forensic method to show how we can retrieve leaked metadata on a running server. Then we propose the use of an Oblivious RAM model as a solution of this leak.Author version Presentation