SBIR-STTR Award

A Game-Theoretic Technology for Protecting ICS against Cyber-Attacks
Award last edited on: 2/10/23

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$255,973
Award Phase
1
Solicitation Topic Code
CA
Principal Investigator
Noah Dunstatter

Company Information

Blocmount Corp

25406 Mesa Crst
San Antonio, TX 78258
   (281) 979-7991
   N/A
   www.blocmount.com
Location: Single
Congr. District: 21
County: Bexar

Phase I

Contract Number: 2150642
Start Date: 9/15/22    Completed: 8/31/23
Phase I year
2022
Phase I Amount
$255,973
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to advance the state of cyber defense in Industrial Control Systems (ICS) that are widely deployed in various sectors such as manufacturing, healthcare, and utilities. This project will develop security cloud services that provide early detection of cyber-attacks and anomalous behaviors. Securing ICS will help guarantee their proper operation and consequently protect human life and equipment as well as conserve resources and materials. This directly benefits society and ensures economic competitiveness of the US through the development of trustworthy and resilient control systems. This Small Business Innovation Research (SBIR) Phase I project will develop a technology solution that provides early detection of cyber-attacks that aim to take over Industrial Control Systems (ICS). The rise of cyber-attacks that use Artificial Intelligence and Machine Learning (AI/ML) techniques poses significant threats to such systems. The solution is composed of (1) an extensible and comprehensive library of check blocks that inspect signals at run-time using state-of-the-art methods from machine learning, statistics, control theory, and time-series analysis; (2) an AI-based defense agent that dynamically applies well-chosen subsets of checks to various signals at run-time; and (3) a cloud service that implements the defense agent. The expected results include game-theoretic models, approximation methods, and reinforcement learning algorithms incorporated in a cloud service that results in effective cyber defense strategies.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.

Phase II

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Start Date: 00/00/00    Completed: 00/00/00
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