Abstract:

Background:
The evolution of medical and health education is intrinsically linked to advances in information technologies (IT). Contemporary educational trends increasingly rely on complex digital ecosystems. As part of this transformation, simulation has evolved from basic mannequins to advanced platforms integrating artificial intelligence (AI), Big Data, and cloud computing, capable of reproducing human physiology and clinical scenarios with realistic accuracy. The integration of high-technology medical simulators, virtual reality (VR), and augmented reality (AR) systems into university educational environments has fundamentally transformed medical education by providing safe conditions for acquiring essential clinical skills without risk to real patients. However, medical simulators operating within Internet of Medical Things (IoMT) environments introduce specific cybersecurity risks due to their network connectivity, raising concerns regarding the security of university infrastructures and the protection of sensitive educational data.
The aim of this study is to explore the critical intersection between medical education and cybersecurity by identifying key cyber risks and attack vectors associated with widely used medical simulation platforms in university settings.

Methods:
The methodology is based on a systematic review of IoMT device architectures deployed in academic simulation environments, combined with an analytical assessment of potential cybersecurity threats. Particularly, attention is given to risks related to unauthorized access, manipulation of training data, and vulnerabilities associated with cloud-based services supporting simulation platforms.

Results:
The research and analysis reveal multiple risk domains, including insufficient network segmentation, inadequate access control mechanisms, exposure through cloud connectivity, and limited cybersecurity awareness among users. A compromised medical simulator may not only lead to sensitive data breaches in violation of data protection regulations (e.g., GDPR), but may also enable the manipulation of clinical scenarios, potentially resulting in the incorrect acquisition of life-saving protocols or erroneous results related to the assessment of the trainees.
In response to these challenges, the study proposes a set of best practices, including network isolation, multi-factor authentication, and the integration of specialized cybersecurity hygiene training into medical and health education curricula for both students and educators.

Conclusions:
Nowadays, cyber-risk in education is not just a technical problem. Cybersecurity in university simulation-based educational environments is no longer solely an IT responsibility, but a key ethical, educational, and policy issue essential for safeguarding the integrity of medical education and the reliability of future clinical practice. Robust cybersecurity policies in the use of medical simulators within educational environments ultimately contribute to the protection of public health and can save lives.

Keywords:

Cybersecurity, technology, IoMT, medical simulation, higher education, data protection, best practices, medical education, public health.