Key Cybersecurity Research Topics & Agenda
The center will strive for creating and generating strong research momentum and agenda. Relevant research topics could include but are not limited to the topics listed in the table below.
| Secure and automate Network focused research | e.g. Wireless, 5G/LTE, etc. |
| Cloud Security & IoT Security | e.g. Machine Learning, augmented learning, DevSecOps |
| Industry 4.0 | e.g. Secure smart manufacturing |
| Human factors in security | e.g. phishing and spam control/mitigation, social engineering attacks, insider attacks, etc. |
| Threat modeling | e.g. Modeling of insider and outsider threats, supply chain security, understanding and managing advanced persistent threats |
| Cyber operations and forensics | e.g. Digital forensics, CyberOp simulations |
| Privacy policy, regulation, legal and ethical issues | e.g. security and privacy regulations, such as, HIPAA, etc. compliance, regulations, etc. |
| Secure software and hardware | e.g. encryption, secure processors, secure OS, secure software engineering, etc. |
| Robotics and artificial intelligence | e.g. cybersecurity threats on robots, security for multi-robot systems, trustworthy AI. |
Internet of Healthcare Things - CNIT Capstone Spring 2022
COVID-19 has caused a profound disruption to the U.S. health care industry. It reveals the challenges the healthcare sector is currently facing as well as new hurdles to overcome. Many technologies have been implemented to fight against COVID-19. One of these technologies is the Internet of Healthcare Things (IoHT), which has used latest technologies in smart biosensors, wearable devices, Internet of Things (IoT), cloud computing, machine learning (ML), and artificial intelligence (AI) to revolutionize healthcare with point-of-care (PoC) diagnostics and enabling the next generation of patient-centric personalized healthcare.
Sponsors
Secure Smart Manufacturing Testbed
Recent innovation within manufacturing has increased the interconnectivity of machines and physical equipment. This enables greater throughput of manufacturing data which can be used to optimize production and reduce human intervention. A Fischertechnik Training Factory 4.0 was used to emulate smart manufacturing technologies including Industrial Internet of Things (IIoT), 5G, Machine Learning (ML) and predictive maintenance within a zero-trust network model.
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