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AI Techniques for Context-Sensitive Tactical Decision Aids

Award Information
Agency: Department of Defense
Branch: Army
Contract: A982-0642
Agency Tracking Number: A982-0642
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 1999
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
1660 S. Amphlett Blvd, Suite 350
San Mateo, CA 94402
United States
DUNS: N/A
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Alexander Davis
 (650) 655-7242
Business Contact
Phone: () -
Research Institution
N/A
Abstract

Not Available Available commercially off the shelf software (COTS) has the potential to address the requirements for an intelligent security agent module. Agent software is designed to be deployed in remote computer systems in order to process at the desired location, or take advantage of available computing resources. Security of agent software is a primary concern for U.S. Government agencies and commercial businesses, including those that are planning to deploy agent-based systems on the Internet. This proposal presents a Phase I project for the implementation of an intelligent agent security module. It describes an approach that utilizes the distributed object middleware of the Object Management Group's (OMG's)Common Object Request Broker Architecture (CORBA) as the basis for secure agent messaging, coupled with available Neural Network agent software from Computer Associates. The goals of this project are; to develop an intelligent security agent module which integrates adaptable wrappers through CORBA facilities, use neural networks for security intrusion detection collection, interpretation, pattern recognition, adaptive learning capabilities and demonstrate an intelligent agent security module to the Navy. The resultant system can provide integrated network administration and security management reducing workload to manage an intelligent agent-based system.

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

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