Columbia University

Gabriela Cretu

Salvatore J Stolfo

Angelos D Keromytis

Angelos Stavrou

Michael E Locasto

Jason Nieh

Stylianos Sidiroglou

Oren Laadan

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.

Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and/or generating sanitized anomaly detection models

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.

Methods, systems and media for software self-healing

Growing community of inventors

New York, NY, United States of America

Gabriela Cretu