SecureNeuroAI: Advanced IT Security for Medical Seizure Detection

The SecureNeuroAI project focuses on developing innovative, IT-secure technologies for the real-time detection of epileptic seizures. The goal is to protect AI-based medical devices from cyberattacks, ensuring the safety of patients and the reliability of medical care.

By integrating multimodal data—including EEG, heart rate, and respiratory rate—the project develops AI models capable of not only accurately detecting seizures but also identifying and mitigating manipulation attempts. Alongside technical innovation, the project emphasizes legal and ethical considerations to safeguard patient data and ensure compliance with regulatory requirements.

We are hiring!

The SecureNeuroAI project is set to begin on July 1st, 2025, and we are seeking a motivated researcher (PhD student or Postdoc) to join our team. The ideal candidate will have a strong background in computer science and machine learning, as well as excellent programming skills. If you are interested in contributing to cutting-edge research at the intersection of AI, cybersecurity, and healthcare, please contact Prof. Björn Krüger via email.

The role of the Krüger group at UKB

The Personalized Digital Health and Telemedicine Group, plays a central role in the project. The group’s contributions include:

  • Data Collection and Analysis: Systematic acquisition of multimodal data in clinical settings, including EEG and vital signs, to create realistic foundations for developing and validating AI models.
  • Development and Integration: Adapting AI models to clinical requirements and integrating them into the IT infrastructure of everyday clinical practice.
  • Pilot Studies: Testing and evaluation of the developed technologies in both clinical and home environments.
  • Interdisciplinary Collaboration: Close collaboration with medical personnel and technical experts to ensure user-friendly and practical solutions.

Collaborations

The project is a collaborative effort with the Computer Science Department at the University of Bonn, involving two leading research groups:

  • The IT Security Group, led by Prof. Dr. Michael Meier, contributing expertise in cybersecurity, risk assessment, and attack detection throughout the AI lifecycle.
  • The Data Science and Intelligent Systems Group, led by Prof. Dr. Elena Demidova, specializing in the development of robust and explainable AI models for multimodal data analysis.

With SecureNeuroAI, we make a significant contribution to improving healthcare and enhancing the resilience of modern medical technologies against cyber threats.

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