SBIR/STTR Research Award

Fooling Computer Vision Classifiers with Adversarial Examples

Award identifier 95104a0cd313b117805bc51287a8d176271e20c69857026f7130ddb2be6d85b9Awarding agency Department of Defense · Navy

Award amount

$124,963

Program and phase

SBIR · Phase I

Award year

2019

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
TRITON SYSTEMS, INC.
Proposal award date
2018-10-15
Contract end date
2019-04-18
UEI
DA91DUWSMSQ7
Solicitation number
18.2
Topic code
N182-127

Research abstract

Triton Systems Inc. propose to create adversarial image techniques that will both fool U.S. classifiers and can applied in operationally relevant physical modification kits to military objects. We will develop a rapid process to generate adversarial images, translate them into physical modification kits and demonstrate a reliable system to camouflage the target object independent of classifier location and type. Our developed system will be used to test U.S. Navy deep neural network computer vision classification systems and to develop an effective counter defense against these physical-world adversarial example attacks.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

927 SBIR/STTR records share this UEI (1993–2026). Reported award amounts total $388,500,403. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Energy, Department of Homeland Security, Department of Health and Human Services, Department of Transportation

Agency intelligence

Department of Defense

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