Text-based cybersecurity attacks classification M/F
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CEA
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Palaiseau, France, Europe

Technically, the internship involves the fields of machine learning (ML) and natural language processing (NLP), and more specifically natural language generation (NLG) and classification techniques. In collaboration with CEA research engineers, the aim will be to train classification models capable of recognizing different types of text-based cyber attacks and distinguishing text-based attacks authored by humans from those generated by AI or by a specific generative model. This internship is meant to be an introduction to research, with the goal of publishing a scientific article if the obtained results are conclusive. The implemented models may also be used to participate in a shared task like AuTexTification (https://sites.google.com/view/autextification/home) and CLIN33 (https://sites.google.com/view/shared-task -clin33/home) or in a challenge like MLMAC (https://mlmac.io/). This work may be followed by a PhD in a broader context.

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