DESC0024986
Project Grant
Overview
Grant Description
Resilient ecosystem for electric vehicle charging systems
Awardee
Grant Program (CFDA)
Awarding Agency
Funding Agency
Place of Performance
Lebanon,
New Hampshire
03766-1441
United States
Geographic Scope
Single Zip Code
Related Opportunity
WEB Sensing was awarded
Project Grant DESC0024986
worth $199,776
from the Office of Science in July 2024 with work to be completed primarily in Lebanon New Hampshire United States.
The grant
has a duration of 9 months and
was awarded through assistance program 81.049 Office of Science Financial Assistance Program.
The Project Grant was awarded through grant opportunity FY 2024 Phase I Release 2.
SBIR Details
Research Type
SBIR Phase I
Title
Resilient Ecosystem for Electric Vehicle Charging Systems
Abstract
C58-01a-281801
We propose to focus on the problem of providing resilient operations to Electric Vehicle Charging Systems (EVCSs) in the face of persistent malicious software threats. Our approach leverages state-of-the- art System-on-Chip (SoC) architectures to monitor, repair, and dynamically alter EVCS binaries from the tightly coupled Field Programmable Logic Array (FPGA) fabric inside the chip-boundary of an SoC. Building from our experience on the DARPA HARDEN and HASH programs, we will develop a heterogenous embedded ecosystem that allows vendorsĺ EVCS software to coexist with innovative security-oriented hardware inference engines. These engines will validate the temporal behavior of EVCS subsystems, detecting potentially malicious implants and intrusions, then restoring the system to a ôgold- standardö image and safe operational state, to mitigate potential attacks. The gold-standard will be constructed such that it does not share an exploitable address with the existing binary, thereby preventing re-infection. The inference engines, and the system behaviors they enforce, are expressed as high-level specifications and behavioral models that are subsequently automatically transformed into FPGA circuit blocks leveraging our enhanced High-Level Synthesis (HLS) technology. The approach is unique in that it leverages the FPGAĺs inherent standing as a bus-master to inspect and modify binaries from a hardware base-of-trust that is invisible to and immutable by malicious implants. This approach has only recently become viable due to maturity of the associated tool chains and the general acceptance of SoCĺs as the core building block for systems integration. The metrics we will use to assess the approach will be based on its ability to operate on any EVCS binary, the time to detect a potential malicious implant, and the time to repair and restructure a designated system binary. Our Phase I effort will focus on the design of a Minimal Viable Product (MVP) for a Resilient Ecosystem that could be utilized in any EVCS. Since our ecosystem rests upon its ability to operate on any arbitrary system binary, irrespective of the vendor, it is the feasibility of this aspect of the system that will be the central focus of the Phase I effort. We plan to explore operating on multiple EVCS software stacks, such as EVerest, in an initial prototype and develop exemplars of models to reflect EVCS behavior. The models will emanate from EVCS software call-graph execution and network interfaces. Web Sensing has, for more than a decade, been a pioneering advocate of resilient systems leveraging novel SoC technologies; our approach has seen continuous evolution at the forefront of several DARPA cyber security efforts, including the CRASH, MRC, AMP, HARDEN, and HASH programs. With experts in automated tools for building FPGA and SoC systems designs, we are uniquely qualified to conduct this application of our existing tools, techniques, and procedures to the domain of EVCS resilience.
Topic Code
C58-01a
Solicitation Number
DE-FOA-0003202
Status
(Complete)
Last Modified 8/27/24
Period of Performance
7/22/24
Start Date
4/21/25
End Date
Funding Split
$199.8K
Federal Obligation
$0.0
Non-Federal Obligation
$199.8K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
DESC0024986
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
892430 SC CHICAGO SERVICE CENTER
Funding Office
892401 SCIENCE
Awardee UEI
PRTXX18CC2N5
Awardee CAGE
71SH2
Performance District
NH-02
Senators
Jeanne Shaheen
Margaret Hassan
Margaret Hassan
Modified: 8/27/24