Avast Software S.r.o.

Ustav Informatiky Av Cr, V.v.i.

Martin Bálek

Martin Vejmelka

Olga Petrova

Ondrej Svec

Dmitry Kuznetsov

Marek Krcál

Fabrizio Biondi

A reference file set having high-confidence malware severity classification is generated by selecting a subset of files from a group of files first observed during a recent observation period and including them in the subset. A plurality of other antivirus providers are polled for their third-party classification of the files in the subset and for their third-party classification of a plurality of files from the group of files not in the subset. A malware severity classification is determined for the files in the subset by aggregating the polled classifications from the other antivirus providers for the files in the subset after a stabilization period of time, and one or more files having a third-party classification from at least one of the polled other antivirus providers that changed during the stabilization period to the subset are added to the subset.

High-confidence malware severity classification of reference file set

A convolutional deep neural network architecture can detect malicious executable files by reading the raw sequence of bytes, that is, without any domain-specific feature extraction or preprocessing.

Malware classification of executable files by convolutional networks

Growing community of inventors

Teplice, Czechia

Martin Bálek