Constructing Shared Latent Semantic Spaces for Malware Detection in the Context of Partial Information

Student: Chistyakov Alexander

Supervisor: Stanislav N. Fedotov

Educational Programme: Data Science (Master)

Final Grade: 9

Year of Graduation: 2020

This article presents the innovative method of constructing the projections of different representations of executable files to the Euclidean probability space and the method for consolidation of any set of constructed latent distributions. The proposed approach could be applied to a wide range of different tasks in the area of cyber-security like optimizing the performance of the automatic pipelines for malware detection, constructing real-time classification models working with any set of file’s artifacts and cyber-crime investigating.

Full text (added May 24, 2020)

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