Development of Cybersecurity Lab Exercises for Mobile Health


  • Hongmei Chi Florida A&M University
  • Meysam Ghaffari Florida State University
  • Ashok Srinivasan University of West Florida
  • Jinwei Liu Florida A&M University


hands-on lab, mHealth app, privacy and security, health data, practical solutions, K-anonymity


There is an emerging class of public health applications where non-health data from mobile apps, such as social media data, are used in subsequent models that identify threats to public health. On one hand, these models require accurate data, which would have an immense impact on public health. On the other hand, results from these models could compromise the privacy of an individual’s health status even without directly using health data. In addition, privacy could also be affected if systems hosting these models are compromised through security breaches. Students ought to be trained in evaluating the effectiveness of different protocols in ensuring privacy while providing useful data to the models. There is a lacuna in current cybersecurity education in training students in the context of both the above types of mobile health applications. The objective of this paper is to describe novel educational material to augment current cybersecurity courses for undergraduate and graduate students. We develop material to teach about fundamental concepts and issues related to security and privacy in mobile health applications and describe a cloud-based hands-on lab that lets students explore the consequences of different solution strategies. Hands-on lab exercises will provide students with insight into the development of practical solutions based on sound theoretical foundations.