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Accurate and Real-time Hardware-assisted Detection of Cyber Attacks through AI/ML

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: 70RSAT23C00000022
Agency Tracking Number: 23.1 DHS231-001-0004-I
Amount: $149,998.92
Phase: Phase I
Program: SBIR
Solicitation Topic Code: DHS231-001
Solicitation Number: 23.1
Timeline
Solicitation Year: 2023
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-05-09
Award End Date (Contract End Date): 2023-10-08
Small Business Information
28 Dana St
Amherst, MA 01002
United States
DUNS: 102221665
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Kristopher Carver
 Technical Director
 (413) 359-0599
 kris@bluerisc.com
Business Contact
 Sylvia Moritz
Title: VPof Finance and Operations
Phone: (617) 517-6324
Email: sylvia@bluerisc.com
Research Institution
N/A
Abstract

With expanded connectivity, the spectrum of devices that are susceptible to cyber-attack is constantly increasing.Beyond this, given the increased processing power and capabilities of everyday IoT/embedded devices, cyber-attacks that previously only targeted endpoints (e.g., botnets, ransomware, DoS, DDoS, etc.) are now broadly applicable.Unfortunately, current cyber-threat detection solutions are still not well suited for heterogeneous computing platforms and are often only applicable to known threat vectors given their signature-driven nature.This inherently gives the attacker an edge over the defender – a dilemma we aim to address with the proposed hardware-assisted cyber-attack detection solution with AI/ML. The proposed solution has broad applicability within DHS, other government agencies as well as commercially.

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

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