AI workflows can improve image-based quality control of agricultural crops
The joint project between DTU and FOSS focuses on how explainable AI can be used for quality control of biological materials – for example, grain, which varies greatly in appearance. The result is not only new insights but also a workflow that can help others develop explainable AI models for biological materials.
The drone industry is ready to protect Denmark – But we need space
Recent drone incursions over Danish airports and military installations have exposed a critical vulnerability in our national security. The political response has been strong: billions of kroner allocated to Danish drone technology. But can Denmark truly become a global leader in this field if the most basic prerequisites are missing? Unfortunately, the answer is no.
An Intelligent Defense Against Hackers
Data normally flows safely through networks, but cyberattacks can subtly disrupt it—often unnoticed. Traditional NIDS based on synthetic data may miss such threats. This project combines machine learning with logic and differentiable logics trained on real data to create monitoring systems with digital intuition that detects even well-hidden attacks.
Threshold Key Management in the Post-Quantum Era: Quantum-Secure Cryptography
In the quantum era, computers will solve mathematical problems far more efficiently, making post-quantum cryptography (PQC) an urgent necessity. The challenge is to make PQC techniques as practical and seamless as today’s cryptographic systems.
This project addresses that challenge by adapting threshold-based key management—where cryptographic keys are shared among multiple parties—to withstand the quantum future.
DIPS in Space: Cybersecurity for satellites
Satellites are vulnerable to cyberattacks. They are deeply interconnected with ground-based systems and are often developed by smaller companies with limited cybersecurity resources. This project addresses this new reality — where satellites form part of the digital frontline, and sophisticated cyberattacks must be detected and mitigated.
Drones to protect Danish power plants in new DIREC project
The DIREC-funded research project PERSIST will introduce autonomous drones to Danish power plants. Equipped with advanced AI, these drones can strengthen the protection of critical infrastructure by continuously monitoring everything from biomass piles to unauthorized intrusions.
Privacy in the Realm of Multilingual Programs: Security in Hybrid Apps
This project aims to develop an analysis tool that enables developers to detect and mitigate vulnerabilities in modern hybrid apps. The project will explore how static code analysis can be combined with dynamic analysis to detect sensitive data flows, for example from Java to JavaScript.
Security by Design for AI Startups: Secure and Scalable AI Agents
In this project, experts from the Alexandra Institute have joined forces with the Danish startup PrivacyMate to close the security gaps introduced by AI agents. The outcome will be an AI agent capable of handling data securely and accurately, as well as a tool that can be deployed internationally.
SECUREAM: Cybersecurity in 3D printing
The project will deliver a comprehensive framework tool that assesses risks and ensures traceability throughout the entire 3D printing process. It also incorporates encryption, allowing partners to share designs without revealing intellectual property. The goal is to enable operators and suppliers to document high-quality production and detect deviations before they escalate into costly errors.
Clearsight: Protecting Denmark’s Digital Infrastructure
The project will develop an intelligent monitoring system for OT (Operational Technology) networks, which are often classified as critical infrastructure. The system continuously checks equipment security, detects suspicious behavior, and alerts the responsible teams when intervention is needed. The goal is to give companies and authorities an early, clear overview of their security posture.