Research Areas
The Cyber Innovation Lab pioneers advancements across nine core domains, addressing critical challenges in the evolving landscape of computer science and cybersecurity.
Cyber Systems Security & Privacy
The security and privacy of sensitive data remain paramount in today’s digital landscape. Through our research in applied cryptography and security, we aim to develop sophisticated cryptographic algorithms and secure communication protocols.
Trustworthy AI in Cybersecurity
We investigate how machine learning can enhance cybersecurity defenses and how to protect AI systems from adversarial attacks. Our work develops intelligent security mechanisms for threat detection while creating novel methodologies to protect AI models.
Decentralized Systems
Our research encompasses foundational architectures and practical applications. Our current research focuses on location-aware cryptography and secure fog computing architectures, integrating blockchain technology to address scalability and security.
Brain-Computer Interfaces
We advance the frontiers of neural computing and its security implications. Our work analyzes methodologies, challenges, and future directions in brain signal decoding while considering privacy and security implications for neural data.
Digital Warfare & Policy
Our research examines the evolving landscape of digital conflicts, defensive strategies, and their implications for national security, developing frameworks for enhancing organizational and national cyber resilience.
Computing Sciences Education
We are committed to advancing cybersecurity education through innovative approaches, including developing advanced machine learning curricula and cyber warfare training bridging academic and military needs.
Cybersecurity in Maritime
Our research addresses the unique vulnerabilities of shipboard networks, autonomous vessels, and port infrastructure. We develop resilient defense mechanisms to protect critical maritime communication systems from sophisticated cyber threats.
Computer Vision
We explore advanced computer vision techniques, focusing on object detection, 3D reconstruction, and visual perception. Our work aims to improve autonomous navigation, anomaly detection, and automated surveillance systems.
Distributed AI
We investigate robust methodologies for distributing AI and machine learning processes across networks, focusing on resilient multi-agent systems and secure edge computing within distributed architectures.