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Hardening data protection using multiple methods rather than 'just' encryption is of paramount importance when considering continuous and powerful attacks in order to observe, steal, alter, or even destroy private and confidential information.Our purpose is to look at cost effective data protection by way of combining fragmentation, encryption, and dispersion over several physical machines. This involves deriving general schemes to protect data everywhere throughout a network of machines where they are being processed, transmitted, and stored during their entire life cycle. This is being enabled by a number of parallel and distributed architectures using various set of cores or machines ranging from General Purpose GPUs to multiple clouds. In this report, we first present a general and conceptual description of what should be a fragmentation, encryption, and dispersion system (FEDS) including a number of high level requirements such systems ought to meet. Then, we focus on two kind of fragmentation. First, a selective separation of information in two fragments a public one and a private one. We describe a family of processes and address not only the question of performance but also the questions of memory occupation, integrity or quality of the restitution of the information, and of course we conclude with an analysis of the level of security provided by our algorithms. Then, we analyze works first on general dispersion systems in a bit wise manner without data structure consideration; second on fragmentation of information considering data defined along an object oriented data structure or along a record structure to be stored in a relational database. |
