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National audienceThe purpose of this paper is the modelization and simulation of zombie machines for the evaluation of Network Intrusion Detection Systems (NIDS), used to detect botnets. We propose an automatic method to infer zombies behaviors through the analysis of messages exchanged with their masters. Once computed, a model provides a solution to generate realistic and manageable traffic, which is mandatory for an NIDS evaluation. We propose to use a Stochastic Mealy Machine to model zombies behavior, and an active inference algorithm to learn it. With our approach, it is possible to generate a realistic traffic corresponding to the communications of botnets while ensuring its controllability in the context of an NIDS evaluation

During the last decade, big data management has attracted increasing interest from both the industrial and academic communities. In parallel, Cyber Security has become mandatory due to various and more intensive threats. In June 2022, a group of researchers has met to reflect on their community's impacts on current research challenges. In particular, they have considered four dimensions: (1) dedicated systems being data processing and analytic platforms or time series management systems; (2) graphs analytics and distributed computation; (3) privacy; and (4) new hardware.

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