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SAFE: Source Agnostic DeepFake Detector
Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8649-21-P-0633
Agency Tracking Number: FX20C-TCSO1-0317
Amount:
$50,000.00
Phase:
Phase I
Program:
STTR
Solicitation Topic Code:
AF20C-TCSO1
Solicitation Number:
X20.C
Timeline
Solicitation Year:
2020
Award Year:
2021
Award Start Date (Proposal Award Date):
2021-02-18
Award End Date (Contract End Date):
2021-05-17
Small Business Information
15400 Calhoun Drive Suite 190
Rockville, MD
20855-2814
United States
DUNS:
161911532
HUBZone Owned:
No
Woman Owned:
No
Socially and Economically Disadvantaged:
No
Principal Investigator
Name: Kemal Davaslioglu
Phone: (301) 294-5208
Email: kdavaslioglu@i-a-i.com
Phone: (301) 294-5208
Email: kdavaslioglu@i-a-i.com
Business Contact
Name: Mark James
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
Name: State University of New York at Buffalo
Contact: Siwei Lyu
Address:
Phone: (716) 645-1587
Type: Nonprofit College or University
Contact: Siwei Lyu
Address:
211 UB Commons, 520 Lee Entrance
Amherst, NY
14228-2567
United States
Phone: (716) 645-1587
Type: Nonprofit College or University
Abstract
We will develop a general DeepFake imagery detection algorithm that uses meta-learning framework to fuse multimodal cues (physiological, signal-level, data-level, and audio-level) to improve detection efficacy. Spatial localization will help identify locations that are more relevant to the detector. Temporal localization will help identify segments of frames to detect videos that are partially tempered. The Source Agnostic DeepFake Detector (SAFE) will provide interpretable results of the inconsistencies in imagery.
* Information listed above is at the time of submission. *
