Deception Studio: Attacker Characterization and Dynamic Relocation

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$745,519.00
Award Year:
2011
Program:
SBIR
Phase:
Phase II
Contract:
FA8650-11-C-1051
Award Id:
n/a
Agency Tracking Number:
O2-1013
Solicitation Year:
2009
Solicitation Topic Code:
OSD09-IA3
Solicitation Number:
2009.2
Small Business Information
105 A Church Street, Madison, AL, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
Y
Duns:
152119025
Principal Investigator:
CodyBuntain
Research Engineer/Dir. of
(256) 325-0010
cody.buntain@pikewerks.com
Business Contact:
SandyRing
Founder&President
(256) 325-0010
sandy.ring@pikewerks.com
Research Institute:
Stub




Abstract
Deception Studio (DS) is a learning, behavior-based defense system for ensuring service availability and trust. DS's learning capabilities include attack detection, prediction, and attribution and can react to attacks in real time by shaping an adversary's perception and creating an illusion capable of manipulating his planning processes. Responses are deployed in a targeted fashion, allowing DS to respond with responses proportionate to the attack without inflicting hard penalties on valid users. Such responses can be both deceptive and active, extending the protection boundary of the system and forcing attackers to react to ever-changing conditions. DS can further provide availability of critical services by moving them out-of-band during ongoing attacks, dynamically migrating an attacker into a decoy environment, or degrading his access while maintaining availability for legitimate users. Before employing such responses, DS includes technology to heal critical services from infection and can also bring this healing technology to bare on compromised systems, returning them to the pool of usable systems. Deception Studio represents the state-of-the-art in active, behavior-based attack detection and prevention systems, imbuing systems with the ability to remain operational, available, and trustworthy through even the most targeted attacks.

* information listed above is at the time of submission.

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