Drexel University

Moshe Kam

Kapil R Dandekar

Raymond Joseph Canzanese, Jr

Spiros Mancoridis

Richard Anthony Primerano

Cole Gindhart

Lit-Hsin Loo

Leonid Hrebien

Ultrasonic through metal communication systems are an effective solution for transmitting data across a metal barrier when the structural integrity of the barrier cannot be compromised by physically penetrating it. Substantial improvements in through metal communication systems have been made in recent years, enabling high speed communications of up to 15 Mbps, as well as power transmission up to 30 W across flat walls. A system is described that allows for ultrasonic through metal communication across the wall of a steel tube. Primary challenges of 1) transducer contact, 2) curvature effect on echoes, and 3) alignment are analyzed and addressed through the use of radial mode piezoelectric transducers, transducer 'horns', and Electromagnetic Acoustic Transducers (EMATs). The resulting system shows no significant loss due to changes in alignment, allows for the use of either piezoelectric transducers or EMATs externally, and achieves max data rates of approximately 600 kbps without echo equalization.

System for ultrasonic communication across curved metal surfaces

A malware detection system and method detects changes in host behavior indicative of malware execution. The system uses linear discriminant analysis (LDA) for feature extraction, multi-channel change-point detection algorithms to infer malware execution, and a data fusion center (DFC) to combine local decisions into a host-wide diagnosis. The malware detection system includes sensors that monitor the status of a host computer being monitored for malware, a feature extractor that extracts data from the sensors corresponding to predetermined features, local detectors that perform malware detection on each stream of feature data from the feature extractor independently, and a data fusion center that uses the decisions from the local detectors to infer whether the host computer is infected by malware.

Multi-channel change-point malware detection

The present invention provides a device and method for removing non-discriminatory indices of an indexed dataset using ensemble statistics analysis. The device may include a data removal module () for removing non-discriminatory indices. For example, the data removal module () may comprise a common characteristic removal module and/or a noise removal module. In addition, the data analyzer () may comprise a normalization means () for normalizing the indexed data. The method of the present invention comprises the steps of identifying and removing portions of the set of data having insufficient discriminatory power based on ensemble statistics of the set of indexed data. For example, the method may include the steps of identifying and removing common characteristics and/or noise portions of the set of indexed data. In addition, the method may comprise the step of normalizing the indexed data either prior to or after the step of removing portions of the set of data.

Apparatus and method for removing non-discriminatory indices of an indexed dataset

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Philadelphia, PA, United States of America

Moshe Kam