Award Abstract # 2229876
AI Institute for Agent-based Cyber Threat Intelligence and Operation

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: UNIVERSITY OF CALIFORNIA, SANTA BARBARA
Initial Amendment Date: May 3, 2023
Latest Amendment Date: August 5, 2024
Award Number: 2229876
Award Instrument: Cooperative Agreement
Program Manager: Dan Cosley
dcosley@nsf.gov
 (703)292-8832
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: June 1, 2023
End Date: May 31, 2028 (Estimated)
Total Intended Award Amount: $19,994,210.00
Total Awarded Amount to Date: $8,278,210.00
Funds Obligated to Date: FY 2023 = $4,336,260.00
FY 2024 = $3,941,950.00
History of Investigator:
  • Giovanni Vigna (Principal Investigator)
    vigna@cs.ucsb.edu
  • Wenke Lee (Co-Principal Investigator)
  • Dongyan Xu (Co-Principal Investigator)
  • Dawn Song (Co-Principal Investigator)
  • Tonya Fields (Co-Principal Investigator)
Recipient Sponsored Research Office: University of California-Santa Barbara
3227 CHEADLE HALL
SANTA BARBARA
CA  US  93106-0001
(805)893-4188
Sponsor Congressional District: 24
Primary Place of Performance: University of California, Santa Barbara
3227 Cheadle Hall, 3rd Floor
Santa Barbara
CA  US  93106-2050
Primary Place of Performance
Congressional District:
24
Unique Entity Identifier (UEI): G9QBQDH39DF4
Parent UEI:
NSF Program(s): AI Research Institutes,
Reimbursable/Reserved Out-year,
AI Institutes - IBM Donation
Primary Program Source: 01002627DB NSF RESEARCH & RELATED ACTIVIT
01002627RB NSF RESEARCH & RELATED ACTIVIT

01002526DB NSF RESEARCH & RELATED ACTIVIT

4082CYXXDB NSF TRUST FUND

01002324RB NSF RESEARCH & RELATED ACTIVIT

01002324DB NSF RESEARCH & RELATED ACTIVIT

01002728RB NSF RESEARCH & RELATED ACTIVIT

01002223RB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002526RB NSF RESEARCH & RELATED ACTIVIT

01002728DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 8237, 075Z
Program Element Code(s): 132Y00, 917900, 253Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Computer systems are increasingly central to national infrastructure in the financial, medical, manufacturing, defense, and other domains. This infrastructure is at risk from sophisticated cyber-adversaries backed by powerful nation-states, whose capabilities rapidly evolve, demanding equally rapid responses. This calls for advances in artificial intelligence and autonomous reasoning that are tightly integrated with advanced security techniques to identify and correct vulnerabilities, detect threats and attribute them to adversaries, and mitigate and recover from attacks. The ACTION Institute will develop novel approaches that leverage artificial intelligence?informed by and working with experts in security operations?to perform security tasks rapidly and at scale, anticipating the moves of an adversary and taking corrective actions to protect the security of computer networks as well as people?s safety. The Institute will function as a nexus for the AI and cybersecurity communities, and its research efforts will be complemented by innovation in education from K-12 to postdoctoral students, the development of new tools for workforce development, and the creation of new opportunities for collaboration among the Institute?s organizations and with external industry partners.

The AI Institute will initiate a revolutionary approach to cybersecurity, in which AI-enabled intelligent security agents cooperate with humans across the cyber-defense life cycle to jointly improve the security posture of complex computer systems over time. Intelligent security agents will follow a new paradigm of continuous, lifelong learning both autonomously and in collaboration with human experts, supported by a shared knowledge bank and an integrated AI stack that provides novel fundamental primitives for (1) reasoning and learning that incorporates domain knowledge, (2) human-agent interaction, (3) multi-agent collaboration, and (4) strategic gaming and tactical planning. Over time, these intelligent security agents will improve their domain knowledge, becoming increasingly robust and effective in the face of changes in the adversaries? modes of operation, composing defense strategies and tactical plans in the presence of uncertainty, collaborating with each other and with humans for mutually complementary teaming, and adapting to unfamiliar and novel attacks.

The Department of Homeland Security and IBM are partnering with NSF to provide funding for this Institute.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Chiang, Chun-Wei and Lu, Zhuoran and Li, Zhuoyan and Yin, Ming "Enhancing AI-Assisted Group Decision Making through LLM-Powered Devil's Advocate" , 2024 https://doi.org/10.1145/3640543.3645199 Citation Details
De_Silva, Ravindu and Guo, Wenbo and Ruaro, Nicola and Grishchenko, Ilya and Kruegel, Christopher and Vigna, Giovanni "GuideEnricher: Protecting the Anonymity of Ethereum Mixing Service Users with Deep Reinforcement Learning" , 2024 Citation Details
Ghazanfar_Abbas, Syed and Ozmen, Muslum Ozgur and Alsaheel, Abdulellah and Khan, Arslan and Celik, Z Berkay and Xu, Dongyan "SAIN: Improving ICS Attack Detection Sensitivity via State-Aware Invariants" , 2024 Citation Details
(Showing: 1 - 10 of 54)

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