Optimizing big data management using conceptual graphs: A mark-based approach

Abstract

Nowadays, the optimization of the representation of big data and their retrieving is actually among the hot studied issues. In this context, this paper proposes a management scheme that enables the representation and the retrieve of big data, even if it is structured or not, based on extended conceptual graphs and the use of structured marks. A case study is given to illustrate the way to represent the generated big data needed to respond to distributed denial of service attacks according to the proposed management scheme and how the querying of such data may help to learn unknown attack fragments. © Springer International Publishing Switzerland 2014.