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Computing with Neural Networks/VadumSecure

Award Information
Agency: Department of Defense
Branch: Office of the Secretary of Defense
Contract: HQ003419P0069
Agency Tracking Number: O182-009-0072
Amount: $224,990.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SCO182-009
Solicitation Number: 18.2
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-02-26
Award End Date (Contract End Date): 2019-08-25
Small Business Information
601 Hutton St STE 109
Raleigh, NC 27606
United States
DUNS: 148551653
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Glen Garner
 Senior Engineer
 (919) 341-8241
Business Contact
 Gary Edge
Phone: (919) 341-8241
Research Institution

Vadum will develop and test Cryptography Hidden In Plain Sight (CHIPS) – a novel technique for secure computing with neural networks used in computer vision applications. The technique transforms any deep convolutional neural network (CNN) operating on data in the plaintext domain into a cryptographically secure equivalent making it resilient to white-box and black-box attacks. Homomorphic encryption schemes are theoretically capable of a similar level of security, but practical implementations introduce noise, latency and complexity preventing widespread adoption. CHIPS can encrypt a CNN of any depth and complexity with secure and straightforward network and data transformations, with minimal impact on speed of inference.

* Information listed above is at the time of submission. *

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