Crowdstrike, Inc.

Mihaela Gaman

Joel Robert Spurlock

Marian Radu

A feature vector is created that comprises a plurality of values, each representing a corresponding portion of a filename extension for a digital file. During an inference workflow of a neural network model, an embedding vector is created that represents, in a meaningful way, the feature vector for the filename extension. A class label prediction value is then computed, based on an evaluation of the embedding vector, a first plurality of embedding vectors representing a plurality of feature vectors for a plurality of benign filename extensions, and a second plurality of embedding vectors representing a plurality of feature vectors for a plurality of malicious filename extensions. A prediction as to whether the digital file has been renamed by a malicious computer program is made, based on the class label prediction value.

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Bucharest, Romania

Mihaela Gaman