Krause, A. F., & Essig, K. (2022). Protecting Privacy Using Low-Cost Data Diodes and Strong Cryptography. In Science and Information Conference (pp. 776-788). Springer, Cham. Abstract Compromised near-body electronic devices, like an eye tracker or a brain-computer interface, can leak private, highly sensitive biometric or medical data. Such data must be protected at all costs to avoid mass-surveillance and hacking attempts. We review the current, dire state of network security caused by complex protocols, closed-source software and proprietary hardware. To tackle the issue, we discuss a concept that protects privacy by combining three elements: data diodes, strong encryption and true random number generators.