Patents by Inventor Ethan M. RUDD

Ethan M. RUDD 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).

  • METHODS AND APPARATUS FOR DETECTION OF MALICIOUS DOCUMENTS USING MACHINE LEARNING
    Publication number: 20240119150
    Abstract: An apparatus for detecting malicious files includes a memory and a processor communicatively coupled to the memory. The processor receives multiple potentially malicious files. A first potentially malicious file has a first file format, and a second potentially malicious file has a second file format different than the first file format. The processor extracts a first set of strings from the first potentially malicious file, and extracts a second set of strings from the second potentially malicious file. First and second feature vectors are defined based on lengths of each string from the associated set of strings. The processor provides the first feature vector as an input to a machine learning model to produce a maliciousness classification of the first potentially malicious file, and provides the second feature vector as an input to the machine learning model to produce a maliciousness classification of the second potentially malicious file.
    Type: Application
    Filed: October 10, 2023
    Publication date: April 11, 2024
    Applicant: Sophos Limited
    Inventors: Joshua Daniel SAXE, Ethan M. RUDD, Richard HARANG
  • Methods and apparatus for detection of malicious documents using machine learning
    Patent number: 11822374
    Abstract: An apparatus for detecting malicious files includes a memory and a processor communicatively coupled to the memory. The processor receives multiple potentially malicious files. A first potentially malicious file has a first file format, and a second potentially malicious file has a second file format different than the first file format. The processor extracts a first set of strings from the first potentially malicious file, and extracts a second set of strings from the second potentially malicious file. First and second feature vectors are defined based on lengths of each string from the associated set of strings. The processor provides the first feature vector as an input to a machine learning model to produce a maliciousness classification of the first potentially malicious file, and provides the second feature vector as an input to the machine learning model to produce a maliciousness classification of the second potentially malicious file.
    Type: Grant
    Filed: May 7, 2021
    Date of Patent: November 21, 2023
    Assignee: Sophos Limited
    Inventors: Joshua Daniel Saxe, Ethan M. Rudd, Richard Harang
  • METHODS AND APPARATUS FOR DETECTION OF MALICIOUS DOCUMENTS USING MACHINE LEARNING
    Publication number: 20210326440
    Abstract: An apparatus for detecting malicious files includes a memory and a processor communicatively coupled to the memory. The processor receives multiple potentially malicious files. A first potentially malicious file has a first file format, and a second potentially malicious file has a second file format different than the first file format. The processor extracts a first set of strings from the first potentially malicious file, and extracts a second set of strings from the second potentially malicious file. First and second feature vectors are defined based on lengths of each string from the associated set of strings. The processor provides the first feature vector as an input to a machine learning model to produce a maliciousness classification of the first potentially malicious file, and provides the second feature vector as an input to the machine learning model to produce a maliciousness classification of the second potentially malicious file.
    Type: Application
    Filed: May 7, 2021
    Publication date: October 21, 2021
    Applicant: Sophos Limited
    Inventors: Joshua Daniel SAXE, Ethan M. RUDD, Richard HARANG
  • Methods and apparatus for detection of malicious documents using machine learning
    Patent number: 11003774
    Abstract: An apparatus for detecting malicious files includes a memory and a processor communicatively coupled to the memory. The processor receives multiple potentially malicious files. A first potentially malicious file has a first file format, and a second potentially malicious file has a second file format different than the first file format. The processor extracts a first set of strings from the first potentially malicious file, and extracts a second set of strings from the second potentially malicious file. First and second feature vectors are defined based on lengths of each string from the associated set of strings. The processor provides the first feature vector as an input to a machine learning model to produce a maliciousness classification of the first potentially malicious file, and provides the second feature vector as an input to the machine learning model to produce a maliciousness classification of the second potentially malicious file.
    Type: Grant
    Filed: January 25, 2019
    Date of Patent: May 11, 2021
    Assignee: Sophos Limited
    Inventors: Joshua Daniel Saxe, Ethan M. Rudd, Richard Harang
  • METHODS AND APPARATUS FOR DETECTION OF MALICIOUS DOCUMENTS USING MACHINE LEARNING
    Publication number: 20190236273
    Abstract: An apparatus for detecting malicious files includes a memory and a processor communicatively coupled to the memory. The processor receives multiple potentially malicious files. A first potentially malicious file has a first file format, and a second potentially malicious file has a second file format different than the first file format. The processor extracts a first set of strings from the first potentially malicious file, and extracts a second set of strings from the second potentially malicious file. First and second feature vectors are defined based on lengths of each string from the associated set of strings. The processor provides the first feature vector as an input to a machine learning model to produce a maliciousness classification of the first potentially malicious file, and provides the second feature vector as an input to the machine learning model to produce a maliciousness classification of the second potentially malicious file.
    Type: Application
    Filed: January 25, 2019
    Publication date: August 1, 2019
    Applicant: Sophos Limited
    Inventors: Joshua Daniel SAXE, Ethan M. RUDD, Richard HARANG