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Tactical Immune System (TIS)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W56KGU-16-C-0065
Agency Tracking Number: A16A-010-0121
Amount: $149,811.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A16A-T010
Solicitation Number: 2016.0
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-09-01
Award End Date (Contract End Date): 2017-02-18
Small Business Information
1236 E. Grant Rd
Tucson, AZ 85719
United States
DUNS: 009731002
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Douglas Kelly
 (520) 829-6981
Business Contact
 Salim Hariri
Phone: (520) 829-6981
Research Institution
 The University of Arizona
 Ali Akoglu
1230 E. Speedway Blvd., \N
Tucson, AZ 85721
United States

 (520) 626-5149
 Nonprofit College or University

Advances in multi-core computing systems, networking, mobile and smart devices, complex software and Internet have enabled the development of revolutionary capabilities that have served many fields across industry, military and academia. However, along with these advances, vulnerabilities in the computing systems stemming from failure to enforce the semantics of computation, have led to an ever increasing number of attacks and their sophistication leading to heavy financial losses and Army mission risks. The current security techniques are mainly labor intensive (e.g., patch update), signature based, and not flexible enough to handle the complexity, dynamism and epidemic-style propagation of attacks. Furthermore, the organization boundaries are gradually disappearing so that the idea of creating a defendable perimeter becomes useless, and on top of that the attackers that we need to protect against, can be corrupted components or software modules within the system and yet who are trusted and have full access to computing system resources and services. Labor intensive are rapidly becoming infeasible in todays technological and data-driven climate. Data are collected at a rate that renders decision-based systems made by humans. Therefore, an autonomous decision making system that can adapt, react, and learn from real-time computer systems cannot be overstated enough.

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

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