Title: ECU-IoHT: A Dataset for Analyzing Cyberattacks in Internet of Health Things
Authors: Mohiuddin Ahmed, Surender Byreddy, Anush Nutakki, Leslie Sikos & Paul Haskell-Dowland
Description: Cyberattacks on the Internet of Health Things (IoHT) are increasingly prevalent, emphasizing the need for effective countermeasures. The development of the ECU-IoHT dataset addresses the critical shortage of publicly available data on IoHT cyberattacks, which is often due to privacy concerns. This dataset, created within an IoHT environment, simulates various attacks to expose multiple vulnerabilities. It serves as a resource for the healthcare security community to analyze attack behaviors and develop more robust countermeasures. Unique in its domain, the ECU-IoHT dataset enables the evaluation of different anomaly detection algorithms, revealing that nearest neighbor-based methods surpass clustering, statistical, and kernel-based approaches in identifying cyberattacks.
Testbed Design: 
Paper URL: https://www.sciencedirect.com/science/article/abs/pii/S1570870521001475