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Modular Analytics and Statistical Quantification of Adversarial Engagements (MASQUERADE)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0834
Agency Tracking Number: N192-129-0106
Amount: $139,970.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N192-129
Solicitation Number: 19.2
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2019-10-21
Award End Date (Contract End Date): 2020-04-21
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
 David Koelle
 Director of Engineering
 (617) 491-3474
Business Contact
 Yvonne Fuller
Phone: (617) 491-3474
Research Institution

Within the past decade, botnets have evolved from simplistic information distributors, which were more of a nuisance than a threat, to complex, weaponized tools that take advantage of cultural values to propagate highly targeted and charged propaganda. Although the ability to detect and map these information campaigns exist, the required capabilities are fragmented across multiple domains of expertise (e.g., knowledge of the campaign, graph and network analytics, and natural language processing). To address the need for analyst-centered tools that identify emerging information campaigns, and allow analysts to keep up with botnets as they evolve over time, we propose to design and demonstrate a Modular Analytics and Statistical Quantification of Adversarial Engagements (MASQUERADE) system. MASQUERADE uses a probabilistic model to maps the complex behaviors expressed by botnets in social networks to the high-level maneuvers carried out by the actors leading for information campaign. MASQUERADE provides analysts the capability to detect information campaigns as they begin, understand the characteristics of a campaign underway, and predict the next steps the campaign will take.

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

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