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Cyber Adversary Discovery Engine (CADE)
Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0351
Agency Tracking Number: N19A-021-0127
Amount:
$139,978.00
Phase:
Phase I
Program:
STTR
Solicitation Topic Code:
N19A-T021
Solicitation Number:
19.A
Timeline
Solicitation Year:
2019
Award Year:
2019
Award Start Date (Proposal Award Date):
2019-06-03
Award End Date (Contract End Date):
2019-12-09
Small Business Information
625 Mount Auburn Street
Cambridge, MA
02138
United States
DUNS:
115243701
HUBZone Owned:
No
Woman Owned:
No
Socially and Economically Disadvantaged:
No
Principal Investigator
Name: Dr. Bryan Loyall Dr. Bryan Loyall
Title: Principal Scientist
Phone: (617) 491-3474
Email: bloyall@cra.com
Title: Principal Scientist
Phone: (617) 491-3474
Email: bloyall@cra.com
Business Contact
Name: Yvonne Fuller
Phone: (617) 491-3474
Email: yfuller@cra.com
Phone: (617) 491-3474
Email: yfuller@cra.com
Research Institution
Name: Northeastern University
Contact: Ms. Susan M. Dorsey Ms. Susan M. Dorsey
Address:
Phone: (617) 373-4600
Type: Nonprofit College or University
Contact: Ms. Susan M. Dorsey Ms. Susan M. Dorsey
Address:
960 Renaissance Park
Boston, MA
02211
United States
Phone: (617) 373-4600
Type: Nonprofit College or University
Abstract
We propose to design and build the Cyber Adversary Discovery Engine (CADE) for forensic cyber analysis. CADE combines expressive behavioral modeling technology with machine learning to automatically recognize adversary behaviors, goals and tactics, techniques and procedures (TTPs). CADE can further automatically recognize changes in adversary TTPs that occur in forensic data. A key technical capability of CADE in addition to its automatic detection capabilities, is its ability to work as an intelligent collaborator with analysts performing forensic cyber analysis, allowing deeper insights and wider analysis than would otherwise be possible.
* Information listed above is at the time of submission. *
