Applying AI to security and securing AI
Applying AI to security and securing AI
Cyber threats and digital warfare are evolving rapidly and changing the face of national security. Our world-class experts explore the latest developments in Artificial Intelligence to both solve emerging cybersecurity challenges and ensure AI-based cyber defense systems remain robust against attacks.
We provide our federal partners with a competitive edge in deploying advanced, resilient AI systems.
We thrive on unsolved challenges
We thrive on unsolved challenges
Our computer scientists and engineers love to analyze emerging challenges and explore unsolved areas of research. Join our team if you want to:
- Research the latest in AI technologies to support national security
- Operationalize LLMs to aid security and intelligence professionals
- Design and deploy AI systems that are not only advanced but also resilient against sophisticated attacks
- Explore reinforcement learning’s profound implications on cybersecurty
- Develop explainable AI algorithms to advance trustworthiness
- Deliver meaningful cybersecurity solutions to federal partners
Research Focus Areas
Large Language Models
Large Language Models
ECTR both uses and defends large language models (LLMs) in the security domain. We are working to bring the benefits of LLMs to the security professional by operationalizing these models for more sophisticated tasks in threat intelligence gathering, malware analysis, and reverse engineering. Yet, LLMs also present attackers with a new attack surface, so we are exploring ways to harden LLMs against data poisoning, prompt injection, data extraction, and other adversarial exploitations.
AI Model Robustness
AI Model Robustness
We develop platforms to ensure and enhance AI model robustness, which is especially critical when these tools are used in national security applications. Robust AI plays a vital role in safeguarding national infrastructure, from communication networks to energy grids, against cyber espionage and sabotage.
Reinforcement Learning for Robust Cyber Defense
Reinforcement Learning for Robust Cyber Defense
Our experts are exploring ways to use reinforcement learning to help defenders identify, contain, and recover from attacks. This approach, a type of machine learning where algorithms learn to make decisions by interacting with an environment, enables AI systems to learn from real-time cyberattacks and adapt their defenses dynamically. Such systems can simulate numerous attack scenarios, continuously learning and improving their defense mechanisms.
Explainable AI
Explainable AI
The ECTR group deploys the latest developments in explainable AI (XAI) to aid cyber defenders. XAI aims to make the often-opaque decision-making processes of AI systems more transparent and understandable to humans. This is crucial in cybersecurity, where understanding the 'why' behind a decision or a prediction is as important as the decision itself. XAI fosters trust among users and stakeholders, ensuring that AI-driven security measures are not just effective, but also accountable.