Patents by Inventor Jeffrey M. Starr

Jeffrey M. Starr 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).

  • Probabilistic model for cyber risk forecasting
    Patent number: 10757127
    Abstract: A system and method are presented for forecasting the risk of cyber-attacks on targeted networks. The described technology quantifies linear and non-linear damages to network-dependent assets by propagating probabilistic distributions of events in sequence and time in order to forecast damages over specified periods. Damage-forecasts are used to estimate probabilistically time-varying financial losses for cyber-attacks. The described technology incorporates quantities and dependencies for pricing insurance, re-insurance, and self-insurance, assessing cost-benefit tradeoffs for sequenced implementation of security control measures, and detecting attacks in the targeted network.
    Type: Grant
    Filed: June 9, 2017
    Date of Patent: August 25, 2020
    Assignee: Neo Prime, LLC
    Inventors: Craig A Schultz, John J. Nitao, Jeffrey M. Starr, John Compton
  • PROBABILISTIC MODEL FOR CYBER RISK FORECASTING
    Publication number: 20170279843
    Abstract: A system and method are presented for forecasting the risk of cyber-attacks on targeted networks. The described technology quantifies linear and non-linear damages to network-dependent assets by propagating probabilistic distributions of events in sequence and time in order to forecast damages over specified periods. Damage-forecasts are used to estimate probabilistically time-varying financial losses for cyber-attacks. The described technology incorporates quantities and dependencies for pricing insurance, re-insurance, and self-insurance, assessing cost-benefit tradeoffs for sequenced implementation of security control measures, and detecting attacks in the targeted network.
    Type: Application
    Filed: June 9, 2017
    Publication date: September 28, 2017
    Inventors: Craig A Schultz, John J. Nitao, Jeffrey M. Starr, John Compton
  • Probabilistic model for cyber risk forecasting
    Patent number: 9680855
    Abstract: A system and method are presented for forecasting the risk of cyber-attacks on targeted networks. The described technology quantifies linear and non-linear damages to network-dependent assets by propagating probabilistic distributions of events in sequence and time in order to forecast damages over specified periods. Damage-forecasts are used to estimate probabilistically time-varying financial losses for cyber-attacks. The described technology incorporates quantities and dependencies for pricing insurance, re-insurance, and self-insurance, assessing cost-benefit tradeoffs for sequenced implementation of security control measures, and detecting attacks in the targeted network.
    Type: Grant
    Filed: June 30, 2014
    Date of Patent: June 13, 2017
    Assignee: NEO PRIME, LLC
    Inventors: Craig A. Schultz, John J. Nitao, Jeffrey M. Starr, John Compton
  • Probabilistic Model For Cyber Risk Forecasting
    Publication number: 20150381649
    Abstract: A system and method are presented for forecasting the risk of cyber-attacks on targeted networks. The described technology quantifies linear and non-linear damages to network-dependent assets by propagating probabilistic distributions of events in sequence and time in order to forecast damages over specified periods. Damage-forecasts are used to estimate probabilistically time-varying financial losses for cyber-attacks. The described technology incorporates quantities and dependencies for pricing insurance, re-insurance, and self-insurance, assessing cost-benefit tradeoffs for sequenced implementation of security control measures, and detecting attacks in the targeted network.
    Type: Application
    Filed: June 30, 2014
    Publication date: December 31, 2015
    Inventors: Craig A. Schultz, John J. Nitao, Jeffrey M. Starr, John Compton