Patents by Inventor Gabriela Cretu

Gabriela Cretu 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).

  • Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and/or generating sanitized anomaly detection models
    Patent number: 8407160
    Abstract: Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and generating anomaly detection models are provided. In some embodiments, methods for generating sanitized data are provided. The methods including: dividing a first training dataset comprised of a plurality of training data items into a plurality of data subsets each including at least one training data item of the plurality of training data items of the first training dataset; based on the plurality of data subsets, generating a plurality of distinct anomaly detection micro-models; testing at least one data item of the plurality of data items of a second training dataset of training data items against each of the plurality of micro-models to produce a score for the at least one tested data item; and generating at least one output dataset based on the score for the at least one tested data item.
    Type: Grant
    Filed: November 15, 2007
    Date of Patent: March 26, 2013
    Assignee: The Trustees of Columbia University in the City of New York
    Inventors: Gabriela Cretu, Angelos Stavrou, Salvatore J. Stolfo, Angelos D. Keromytis, Michael E. Locasto
  • Methods, systems and media for software self-healing
    Patent number: 7962798
    Abstract: Methods, systems, and media for enabling a software application to recover from a fault condition, and for protecting a software application from a fault condition, are provided. In some embodiments, methods include detecting a fault condition during execution of the software application, restoring execution of the software application to a previous point of execution, the previous point of execution occurring during execution of a first subroutine in the software application, and forcing the first subroutine to forego further execution and return to a caller of the first subroutine.
    Type: Grant
    Filed: April 17, 2007
    Date of Patent: June 14, 2011
    Assignee: The Trustees of Columbia University in the City of New York
    Inventors: Michael E. Locasto, Angelos D. Keromytis, Salvatore J. Stolfo, Angelos Stavrou, Gabriela Cretu, Stylianos Sidiroglou, Jason Nieh, Oren Laadan
  • Methods, systems and media for software self-healing
    Publication number: 20100011243
    Abstract: Methods, systems, and media for enabling a software application to recover from a fault condition, and for protecting a software application from a fault condition, are provided. In some embodiments, methods include detecting a fault condition during execution of the software application, restoring execution of the software application to a previous point of execution, the previous point of execution occurring during execution of a first subroutine in the software application, and forcing the first subroutine to forego further execution and return to a caller of the first subroutine.
    Type: Application
    Filed: April 17, 2007
    Publication date: January 14, 2010
    Applicant: THE TRUSTEES OF COLUMBIA UNIVERSITY
    Inventors: Michael E. Locasto, Angelos D. Keromytis, Salvatore J. Stolfo, Angelos Stavrou, Gabriela Cretu, Stylianos Sidiroglou, Jason Nieh, Oren Laadan
  • SYSTEMS, METHODS, AND MEDIA FOR GENERATING SANITIZED DATA, SANITIZING ANOMALY DETECTION MODELS, AND/OR GENERATING SANITIZED ANOMALY DETECTION MODELS
    Publication number: 20080262985
    Abstract: Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and generating anomaly detection models are provided. In some embodiments, methods for generating sanitized data are provided. The methods including: dividing a first training dataset comprised of a plurality of training data items into a plurality of data subsets each including at least one training data item of the plurality of training data items of the first training dataset; based on the plurality of data subsets, generating a plurality of distinct anomaly detection micro-models; testing at least one data item of the plurality of data items of a second training dataset of training data items against each of the plurality of micro-models to produce a score for the at least one tested data item; and generating at least one output dataset based on the score for the at least one tested data item.
    Type: Application
    Filed: November 15, 2007
    Publication date: October 23, 2008
    Inventors: Gabriela CRETU, Angelos STAVROU, Salvatore J. STOLFO, Angelos D. KEROMYTIS, Michael E. LOCASTO