Patents by Inventor Michael E. Locasto

Michael E. Locasto 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: 7784097
    Abstract: Systems and methods for correlating and distributing intrusion alert information among collaborating computer systems are provided. These systems and methods provide an alert correlator and an alert distributor that enable early signs of an attack to be detected and rapidly disseminated to collaborating systems. The alert correlator utilizes data structures to correlate alert detections and provide a mechanism through which threat information can be revealed to other collaborating systems. The alert distributor uses an efficient technique to group collaborating systems and then pass data between certain members of those groups according to a schedule. In this way data can be routinely distributed without generating excess traffic loads.
    Type: Grant
    Filed: November 24, 2004
    Date of Patent: August 24, 2010
    Assignee: The Trustees of Columbia University in the City of New York
    Inventors: Salvatore J. Stolfo, Angelos D. Keromytis, Vishal Misra, Michael E. Locasto, Janak Parekh
  • Publication number: 20100146615
    Abstract: In accordance with some embodiments of the present invention, systems and methods that protect an application from attacks are provided. In some embodiments of the present invention, input from an input source, such as traffic from a communication network, can be routed through a filtering proxy that includes one or more filters, classifiers, and/or detectors. In response to the input passing through the filtering proxy to the application, a supervision framework monitors the input for attacks (e.g., code injection attacks). The supervision framework can provide feedback to tune the components of the filtering proxy.
    Type: Application
    Filed: April 21, 2006
    Publication date: June 10, 2010
    Inventors: Michael E. Locasto, Salvatore J. Stolfo, Angelos D. Keromytis, Ke Wang
  • 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
  • Publication number: 20090144827
    Abstract: The claimed subject matter provides a system and/or method that generates data patches for vulnerabilities. The system can include devices and components that examine exploits received or obtained from data streams, constructs probes and determines whether the probes take advantage of vulnerabilities. Based at least in part on such determinations data patches are dynamically generated to remedy the hitherto vulnerabilities.
    Type: Application
    Filed: November 30, 2007
    Publication date: June 4, 2009
    Applicant: MICROSOFT CORPORATION
    Inventors: Marcus Peinado, Weidong Cui, Jiahe Helen Wang, Michael E. Locasto
  • 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