Military Embedded Systems

Secure neural network developed for Secretary of Defense


November 13, 2019

Emma Helfrich

Technology Editor

Military Embedded Systems

CAMBRIDGE, Mass. Charles River Analytics Inc., developer of intelligent systems solutions, has received funding from the Strategic Capabilities Office of the Secretary of Defense (OSD) to develop a Secure Private Neural Network (SPNN) that hardens deep neural networks against adversary attacks.

The U.S. government relies on deep neural networks for critical machine learning tasks — the OSD Strategic Capabilities Office is concerned with both black box and white box attacks on a deep neural network.

SPNN is intended to provide privacy and security for analysts training deep neural networks to perform inference on big data. These networks learn using training datasets that may contain sensitive data; adversaries can exploit these networks, causing data breaches or misclassification of sensitive information.

According to the company, SPNN will produce a secure neural network to preserve the privacy of training and testing data against white box attacks via end-to-end efficient encryption. Additional obfuscation defenses thwart black box attacks by adversaries who gain unencrypted access to the deep neural network through subversion or misuse of the system to conduct chosen plaintext attacks.



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