CIC IoMT dataset 2024

The CICIoMT2024 dataset is a comprehensive dataset designed for cybersecurity research focused on the Internet of Medical Things (IoMT). Developed by the Canadian Institute for Cybersecurity, it simulates realistic IoMT network traffic, representing the diverse and evolving threats faced by connected healthcare devices. The dataset comprises network traffic data from various IoMT devices, with labeled instances for 18 distinct types of cyberattacks, alongside benign traffic data.

Each cyberattack type is meticulously crafted to reflect common and advanced threats, such as Distributed Denial of Service (DDoS), ransomware, man-in-the-middle attacks, and malware injections. With a balanced mix of attacks and benign instances, CICIoMT2024 enables robust training and testing for various cybersecurity models.

The CICIoMT2024 dataset’s detailed packet-level information and multi-class labels make it ideal for developing and evaluating machine learning and deep learning algorithms. Its design emphasizes real-world application, making it a valuable resource for researchers aiming to enhance IoMT security, protect patient data, and ensure the resilience of medical networks against cyber threats.