Patents by Inventor Martin Bálek

Martin Bálek has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • High-confidence malware severity classification of reference file set
    Patent number: 11861006
    Abstract: 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.
    Type: Grant
    Filed: January 18, 2021
    Date of Patent: January 2, 2024
    Assignee: Avast Software s.r.o.
    Inventors: Martin Bálek, Fabrizio Biondi, Dmitry Kuznetsov, Olga Petrova
  • HIGH-CONFIDENCE MALWARE SEVERITY CLASSIFICATION OF REFERENCE FILE SET
    Publication number: 20220229906
    Abstract: 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.
    Type: Application
    Filed: January 18, 2021
    Publication date: July 21, 2022
    Applicant: Avast Software s.r.o.
    Inventors: Martin Bálek, Fabrizio Biondi, Dmitry Kuznetsov, Olga Petrova
  • Malware classification of executable files by convolutional networks
    Patent number: 11256804
    Abstract: 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.
    Type: Grant
    Filed: November 8, 2018
    Date of Patent: February 22, 2022
    Assignees: Avast Software s.r.o., Ustav informatiky AV CR, v.v.i.
    Inventors: Marek Kr{hacek over (c)}ál, Martin Bálek, Ond{hacek over (r)}ej {hacek over (S)}vec, Martin Vejmelka
  • MALWARE CLASSIFICATION OF EXECUTABLE FILES BY CONVOLUTIONAL NETWORKS
    Publication number: 20190138722
    Abstract: 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.
    Type: Application
    Filed: November 8, 2018
    Publication date: May 9, 2019
    Inventors: Marek Krcál, Martin Bálek, Ondrej Svec, Martin Vejmelka