Background: The privacy and security of a person's health data is a human right protected by law in many countries. However, networked information systems that store and process health data may have security vulnerabilities and are attractive to attacks aimed to gain either unauthorized access to these data or compromise it. Compromising data of patients with chronic conditions like Diabetes Mellitus has potentially life-threatening consequences (e.g., from incorrect insulin dosing due to loss of glucose measurement data integrity). Consequently, privacy-preserving computing methods are called to mitigate the risk of a data breach.

Methods: In this paper, our aim is to apply homomorphic encryption to safeguard blood glucose management in the context of artificial pancreas device systems. Namely, we introduced and evaluated a proportional- integral-derivative controller using simulation tests. We compared a plaintext controller with the proposed privacy-preserving controller on two different food-intake profiles.

Results: Our results demonstrated that the time in range values by our system (the average time in range across 10 average food intake profiles and 10 extreme profiles were 85.9% and 86.0%, respectively) did not differ between the two implementations.

Conclusion: In the future, a cloud-based secure, and private Diabetes Mellitus management system of this kind could both regulate a given patient's blood glucose and support remote patient monitoring continuously and conveniently at home.