2415318
Project Grant
Overview
Grant Description
SBIR Phase I: Continuous identity verification via wearable neural interfaces
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enhance digital security by integrating continuous biometric authentication into all human-computer interactions.
The World Economic Forum cites widespread cyber-crime among the top 10 most severe global risks, with widespread impact on private industry, critical infrastructure, and cyber warfare.
Recent developments in artificial intelligence compound these risks, with “deepfake” technology and large language models producing highly convincing fraudulent communications that easily bypass human scrutiny.
This project develops and evaluates a new form of real-time authentication based on a novel biometric sensing approach that can secure every interaction an individual has with digital systems.
At scale, the technology can mitigate cyber threats to secured systems by continuously certifying the authenticity of human-computer interactions.
This Small Business Innovation Research (SBIR) Phase I project will commercialize a fundamentally new biometric authentication approach for secure human-computer interaction.
When interfacing with digital technology, there is no direct link between a user’s actions and their identity.
Current approaches to solve this problem (e.g., usernames, passwords, biometrics) are imperfect, presenting a major weak point in digital security that is commonly exploited.
As humans interact with technology, their hand movements and posture arise from unique neuromuscular activity patterns that could be used for real-time identity verification.
This project develops sensing technology to capture these unique signals to create a new kind of continuous, biometric authentication.
This approach essentially provides a user-specific “watermark” that the wearer’s actions (keystrokes, gestures, etc.) are authentic and authorized.
Real-time user verification can streamline the authentication process and overcome core vulnerabilities in legacy approaches that make them susceptible to compromise, setting the stage for secure and intuitive human-machine interfacing.
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.
Subawards are not planned for this award.
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enhance digital security by integrating continuous biometric authentication into all human-computer interactions.
The World Economic Forum cites widespread cyber-crime among the top 10 most severe global risks, with widespread impact on private industry, critical infrastructure, and cyber warfare.
Recent developments in artificial intelligence compound these risks, with “deepfake” technology and large language models producing highly convincing fraudulent communications that easily bypass human scrutiny.
This project develops and evaluates a new form of real-time authentication based on a novel biometric sensing approach that can secure every interaction an individual has with digital systems.
At scale, the technology can mitigate cyber threats to secured systems by continuously certifying the authenticity of human-computer interactions.
This Small Business Innovation Research (SBIR) Phase I project will commercialize a fundamentally new biometric authentication approach for secure human-computer interaction.
When interfacing with digital technology, there is no direct link between a user’s actions and their identity.
Current approaches to solve this problem (e.g., usernames, passwords, biometrics) are imperfect, presenting a major weak point in digital security that is commonly exploited.
As humans interact with technology, their hand movements and posture arise from unique neuromuscular activity patterns that could be used for real-time identity verification.
This project develops sensing technology to capture these unique signals to create a new kind of continuous, biometric authentication.
This approach essentially provides a user-specific “watermark” that the wearer’s actions (keystrokes, gestures, etc.) are authentic and authorized.
Real-time user verification can streamline the authentication process and overcome core vulnerabilities in legacy approaches that make them susceptible to compromise, setting the stage for secure and intuitive human-machine interfacing.
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.
Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Berkeley,
California
94708-1603
United States
Geographic Scope
Single Zip Code
Morphosis was awarded
Project Grant 2415318
worth $275,000
from National Science Foundation in September 2024 with work to be completed primarily in Berkeley California United States.
The grant
has a duration of 5 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I: Continuous Identity Verification via Wearable Neural Interfaces
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enhance digital security by integrating continuous biometric authentication into all human-computer interactions. The World Economic Forum cites widespread cyber-crime among the top 10 most severe global risks, with widespread impact on private industry, critical infrastructure, and cyber warfare. Recent developments in artificial intelligence compound these risks, with “deepfake” technology and Large Language models producing highly convincing fraudulent communications that easily bypass human scrutiny. This project develops and evaluates a new form of real-time authentication based on a novel biometric sensing approach that can secure every interaction an individual has with digital systems. At scale, the technology can mitigate cyber threats to secured systems by continuously certifying the authenticity of human-computer interactions.
This Small Business Innovation Research (SBIR) Phase I project will commercialize a fundamentally new biometric authentication approach for secure human-computer interaction. When interfacing with digital technology, there is no direct link between a user’s actions and their identity. Current approaches to solve this problem (e.g., usernames, passwords, biometrics) are imperfect, presenting a major weak point in digital security that is commonly exploited. As humans interact with technology, their hand movements and posture arise from unique neuromuscular activity patterns that could be used for real-time identity verification. This project develops sensing technology to capture these unique signals to create a new kind of continuous, biometric authentication. This approach essentially provides a user-specific “watermark” that the wearer’s actions (keystrokes, gestures, etc.) are authentic and authorized. Real-time user verification can streamline the authentication process and overcome core vulnerabilities in legacy approaches that make them susceptible to compromise, setting the stage for secure and intuitive human-machine interfacing.
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.
Topic Code
CA
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 9/17/24
Period of Performance
9/1/24
Start Date
2/28/25
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2415318
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
GP1SFMCM9GF3
Awardee CAGE
9QA03
Performance District
CA-12
Senators
Dianne Feinstein
Alejandro Padilla
Alejandro Padilla
Modified: 9/17/24