DeepDefenseA Deep-Learning based Cyber Defense System

DeepDefenseA Deep-Learning based Cyber Defense System

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-18-C-0131
Agency Tracking Number: F173-002-0261
Amount: $150,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2018
Solicitation Year: 2017
Solicitation Topic Code: AF173-002
Solicitation Number: 2017.3
Small Business Information
15400 Calhoun Drive, Rockville, MD, 20855
DUNS: 161911532
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Guang Jin
 (301) 294-4257
 gjin@i-a-i.com
Business Contact
 Mark James
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
N/A
Abstract
It has been observed that cyber-attacks are increasing in both prevalence and sophistication. Most existing cyber defense systems are still using the aged signature-matching techniques which can be easily avoided by current malware through polymorphic methods, such as obfuscation. In this effort, IAI proposes to develop DeepDefense, a deep-learning based cyber defense system to effectively detect and mitigate zero-day attacks. DeepDefense detects zero-day cyber-attacks by analyzing the software program behaviors which cannot be evaded by any polymorphic methods. DeepDefense utilizes a deep-learning based artificial intelligence method to automatically identify benign and malicious behaviors. DeepDefense will be implemented and run at the host end. Thus DeepDefense is network agnostic, and can provide uninterrupted security protection even under an encrypted network environment. The intrusion detection results from DeepDefense can be easily reported to an existing SIEM system to improve the security capabilities of mitigating zero-day attacks. Together, DeepDefense will provide advanced intrusion detection/mitigation capabilities to enterprise networks, and provide continuous and uninterrupted security protection against zero-day attacks.

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

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