Current SecureAmerica Institute projects as part of a nationwide initiative to empower a secure and resilient U.S. manufacturing and defense industrial base.
Partner Organization: Deloitte
Vital industrial bases no longer have any domestic presence creating a gap in an American ability to remain resilient during potential disruptions. Deep View will conduct a multi-tier supply chain and industrial base assessment to evaluate the technology readiness levels of interconnection security within the selected manufacturing industrial base. Project findings will be incorporated into SAI’s long-term engagement plan with industry members and raise industrial base and supply chain analysis where collective influence of SAI members can inform industry-wide risk mitigation efforts.
A Sensor Fusion Modeling and Simulation Framework for Decision Support
Partner Organization: Amentum Contributing Partner: Unity3d
Few tools allow for the intuitive creation of sensor models which can then be tested across any number of scenario configurations. This project will explore an approach to leverage existing advanced sensor fusion modeling with an easy to use graphical user interface helping designers, operators, and practitioners to analyze and predict sensor-fusion based scenarios.
Achieving Resilience Against Insider Threats in IT/OT Networks via Defensive Deception
Partner Organization: North Carolina State University
Improvements in manufacturing agility and flexibility through automation are needed to ensure security and resilience in information technology and operational technology networks. This project will develop solutions to achieve resilience by resisting attacks, detecting attacks in progress, and ensuring an IT/OT system can automatically restore itself to a trusted state and continue operation.
Sensitivity Analysis of AM Process Improvements for Hypersonic Propulsion Systems
Partner Organization: Ursa Major Technologies
Contributing Partners: ExOne, CvDTEK, AFRL
Direct Laser Metal Sintering (DMLS) is a powerful manufacturing approach to creating high-performing propulsion systems for hypersonics, but is limited by the speed a component may be produced. This project will create a sensitivity analysis of a set of approaches to increase the security of additive manufacturing supply chains by improving the yield and throughput speed.
Readiness Assessment of Supplier Digitization
Partner Organization: Morgan State University
Emerging needs and vulnerabilities in the manufacturing and defense industrial base supply chain cannot be identified without evaluating supply chain participants’ current digital maturity level across the six digitization pillars of digital development. This project will survey partners to determine the readiness of supply chain participants for satisfying the six pillars (digital development, synchronized planning, intelligent supply, smart factory, dynamic fulfillment, connected customer) to analyze and prepare a digital supply chain framework for participants.
Methodology for Predicting and Validating the Trustworthiness of Robots
Partner Organization: Ohio State University
Increase in automation, specifically industrial robots, has created new access points for cybersecurity vulnerabilities in industrial internet of things (IIoT) components. This project will develop an external system consisting of sensing and human operator observations to predict when loss of trust will occur in robotic systems and identify behavior that may indicate a cyber intrusion.
A Taxonomy Driven Approach to Realize Built-In Security of Manufacturing Supply Chains
Partner Organization: New York University
Contributing Partner: Siemens
Cybersecurity by system design considerations are needed to enhance the testing and assure the built-in cybersecurity in emerging supply management chains. This project will build a global, scalable, crowdsourcing tool to help certify cybersecurity postures for all aspects of supply management systems.
Resilient Additive Manufacturing Program (RAMP)
Partner Organization: Raytheon Technologies Research Center
Contributing Partner: Georgia Institute of Technology
Additive manufacturing platforms are particularly vulnerable to cyber-attack since occurred attacks easily be mistaken as process or part defects due to inherent process variability. This project will focus on the development of machine learning based algorithms and tools to enable cyber-physical manufacturing systems to differentiate between faulty and compromised products.
From Device to Cloud: An End-To-End Framework for Trusted Edge Computing for Industrial Internet of Things (IIoT) Security
Partner Organization: University of Texas at Dallas
Due to growing adoption of IIoT devices and edge computing, currently employed security solutions are insufficient to thwart strong adversaries from stealing and manipulating sensitive data. This project will develop a new trusted execution environment to enable end-to-end data protection and prevent theft of sensitive data.