Patents by Inventor Jason A. Laska

Jason A. Laska 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).

  • Patent number: 10929529
    Abstract: A cyber-security threat detection system and method stores physical data measurements from a cyber-physical system and extracts synchronized measurement vectors synchronized to one or more timing pulses. The system and method synthesize data integrity attacks in response to the physical data measurements and applies alternating parameterized linear and non-linear operations in response to the synthesized data integrity attacks. The synthesis renders optimized model parameters used to detect multiple cyber-attacks.
    Type: Grant
    Filed: January 28, 2020
    Date of Patent: February 23, 2021
    Assignee: UT-BATTELLE, LLC
    Inventors: Erik M. Ferragut, Jason A. Laska
  • Publication number: 20200226251
    Abstract: A cyber-security threat detection system and method stores physical data measurements from a cyber-physical system and extracts synchronized measurement vectors synchronized to one or more timing pulses. The system and method synthesize data integrity attacks in response to the physical data measurements and applies alternating parametrized linear and non-linear operations in response to the synthesized data integrity attacks. The synthesis renders optimized model parameters used to detect multiple cyber-attacks.
    Type: Application
    Filed: January 28, 2020
    Publication date: July 16, 2020
    Inventors: Erik M. Ferragut, Jason A. Laska
  • Patent number: 10572659
    Abstract: A cyber-security threat detection system and method stores physical data measurements from a cyber-physical system and extracts synchronized measurement vectors synchronized to one or more timing pulses. The system and method synthesizes data integrity attacks in response to the physical data measurements and applies alternating parametrized linear and non-linear operations in response to the synthesized data integrity attacks. The synthesis renders optimized model parameters used to detect multiple cyber-attacks.
    Type: Grant
    Filed: September 19, 2017
    Date of Patent: February 25, 2020
    Assignee: UT-Battelle, LLC
    Inventors: Erik M. Ferragut, Jason A. Laska
  • Publication number: 20180082058
    Abstract: A cyber-security threat detection system and method stores physical data measurements from a cyber-physical system and extracts synchronized measurement vectors synchronized to one or more timing pulses. The system and method synthesizes data integrity attacks in response to the physical data measurements and applies alternating parametrized linear and non-linear operations in response to the synthesized data integrity attacks. The synthesis renders optimized model parameters used to detect multiple cyber-attacks.
    Type: Application
    Filed: September 19, 2017
    Publication date: March 22, 2018
    Inventors: Erik M. Ferragut, Jason A. Laska
  • Patent number: 9361463
    Abstract: A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.
    Type: Grant
    Filed: December 11, 2013
    Date of Patent: June 7, 2016
    Assignee: UT-Batelle, LLC
    Inventors: Erik M. Ferragut, Jason A. Laska, Robert A. Bridges
  • Patent number: 9319421
    Abstract: A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.
    Type: Grant
    Filed: October 14, 2013
    Date of Patent: April 19, 2016
    Assignee: UT-Battelle, LLC
    Inventors: Erik M. Ferragut, John R. Goodall, Michael D. Iannacone, Jason A. Laska, Lane T. Harrison
  • Publication number: 20150161394
    Abstract: A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.
    Type: Application
    Filed: December 11, 2013
    Publication date: June 11, 2015
    Applicant: UT-Battelle, LLC
    Inventors: Erik M. Ferragut, Jason A. Laska, Robert A. Bridges
  • Publication number: 20150106927
    Abstract: A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.
    Type: Application
    Filed: October 14, 2013
    Publication date: April 16, 2015
    Applicant: UT-Battelle, LLC
    Inventors: Erik M. Ferragut, John R. Goodall, Michael D. Iannacone, Jason A. Laska, Lane T. Harrison