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BotMesh

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N66001-11-P-5120
Agency Tracking Number: N111-083-0074
Amount: $79,921.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N111-083
Solicitation Number: 2011.1
Timeline
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-05-23
Award End Date (Contract End Date): N/A
Small Business Information
33 Thornwood Drive, Suite 500
Ithaca, NY -
United States
DUNS: 101321479
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Stephen Brueckner
 Technical Director
 (607) 257-1975
 steve@atc-nycorp.com
Business Contact
 Richard Smith
Title: Controller
Phone: (607) 257-1975
Email: rick@atc-nycorp.com
Research Institution
 Stub
Abstract

Botnets and other large-scale malicious behaviors present a pervasive and evolving threat to cyber security. Stealth botnets and distributed, stealthy cyber attacks present a particular challenge to cyber defense because their malicious behavior is difficult to detect. State-of-the-art and next-generation cyber security algorithms will be capable of detecting and preventing stealthy and distributed cyber attacks. Effectively using these algorithms requires a network security infrastructure capable of collecting network traffic information for a large number of networks over long periods of time, making decisions based on accumulated network traffic information, and implementing new policies on network security hardware. ATC-NY will develop BotMesh, a network sensor infrastructure and framework for cyber security algorithms. The BotMesh architecture manages the collection and storage of filtered network traffic information from a large, distributed collection of network sensors, the application of computationally-intensive algorithms to collected data, visualization and decision-making based on the results of these algorithms, and the alteration of network security policies in response to identified threats. With BotMesh, a future algorithm to detect a type of stealthy botnet attack can be rapidly implemented and deployed on an existing network of sensors, quickly detecting, identifying, and defending against hostile stealth botnets and similar threats.

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

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