Hewlett Packard Enterprise Development LP

Raytheon Technologies Corporation

Madhusudana Shashanka

Michael J Giering

Jisheng Wang

Vivek Venugopalan

Min-Yi Shen

Soumik Sarkar

Chao Yang

A method includes converting time-series data from a plurality of prognostic and health monitoring (PHM) sensors into frequency domain data. One or more portions of the frequency domain data are labeled as indicative of one or more target modes to form labeled target data. A model including a deep neural network is applied to the labeled target data. A result of applying the model is classified as one or more discretized PHM training indicators associated with the one or more target modes. The one or more discretized PHM training indicators are output.

Sensor data fusion for prognostics and health monitoring

A security appliance with one or more processors and a memory communicatively coupled to the one or more processors is described. The memory includes behavior profiling service logic that, when executed by the one or more processors, (i) creates a behavior profile for a particular entity based on received incoming data, and (ii) determines whether the behavior profile identifies that a malicious attack is being performed by the particular entity based on a comparison of the behavior profile to a reference profile. The reference profile represents historical behavior of the particular entity that is monitored over a prescribed period of time.

System and method directed to behavioral profiling services

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Santa Clara, CA, United States of America

Madhusudana Shashanka