Integrating Zero-Trust Principles into IIoT Architectures for Enhanced Security
Monthly Member Meeting - Virtual
Friday, May 24, 2024
While zero-trust architectures have been employed for networks and data centers for years, our research focuses on integrating zero-trust principles into Industrial Internet of Things (IIOT) architectures.
Zero-trust architectures can be integrated into IIoT architectures to enhance system security using resilience and security metrics that enable full-scale system validation and evidence-based security assurances.
This research facilitates the modeling of smart building systems through lightweight devices and the creation of graph representations of industrial processes based on multi-disciplinary schemas. These processes have been analyzed using zero-trust architecture principles through the development of many new tools centered around codified attack surfaces and describing the system with quality data.
Finally, this research focuses on traceable data and graph-based data analysis strategies, thereby creating a flexible data analytics toolkit for IIoT systems including AI/ML models.
Presenter:
Dr. Shaya P. Wolf, Idaho National Laboratory
This event is funded by the National Science Foundation grant #2054724.
X-ALT-DESC;FMTTYPE=text/html:Integrating Zero-Trust Principles into IIoT Architectures for Enhanced Security
Monthly Member Meeting - Virtual
Friday, May 24, 2024
While zero-trust architectures have been employed for networks and data centers for years, our research focuses on integrating zero-trust principles into Industrial Internet of Things (IIOT) architectures.
Zero-trust architectures can be integrated into IIoT architectures to enhance system security using resilience and security metrics that enable full-scale system validation and evidence-based security assurances.
This research facilitates the modeling of smart building systems through lightweight devices and the creation of graph representations of industrial processes based on multi-disciplinary schemas. These processes have been analyzed using zero-trust architecture principles through the development of many new tools centered around codified attack surfaces and describing the system with quality data.
Finally, this research focuses on traceable data and graph-based data analysis strategies, thereby creating a flexible data analytics toolkit for IIoT systems including AI/ML models.
Presenter:
Dr. Shaya P. Wolf, Idaho National Laboratory
This event is funded by the National Science Foundation grant #2054724.
LOCATION:Virtual\, CLASS:PUBLIC END:VEVENT END:VCALENDAR