Siemens Medical Solutions Usa, Inc.

Northeastern University

Jennifer Dy

Glenn Fung

Romer E Rosales

Aviram Cohen

David Kaeli

Micha Moffie

Fatemeh Azmandian

Yan Yan

Javed Aslam

Malak Alshawabkeh

An intrusion detection system collects architectural level events from a Virtual Machine Monitor where the collected events represent operation of a corresponding Virtual Machine. The events are consolidated into features that are compared with features from a known normal operating system. If an amount of any differences between the collected features and the normal features exceeds a threshold value, a compromised Virtual Machine may be indicated. The comparison thresholds are determined by training on normal and abnormal systems and analyzing the collected events with machine learning algorithms to arrive at a model of normal operation.

VMM-based intrusion detection system

A method, including receiving multi-labeler data that includes data points labeled by a plurality of labelers; building a model from the multi-labeler data, wherein the model includes an input variable that corresponds to the data points, a label variable that corresponds to true labels for the data points, and variables for the labels given by the labelers; and executing the model, in response to receiving new data points, to determine a level of expertise of the labelers for the new data points.

Automatic labeler assignment using a model built from multi-labeler data

Growing community of inventors

Framingham, MA, United States of America

Jennifer Dy