IoTCloak: Practical Integrity Checks of Machine Learning Inference Code and Models on Tiny IoT Devices

IoT devices comprising single-core ARM Cortex-M micro-controllers were earlier used in simple interfacing boards for different sensors. They have come a long way and currently process sensor data using powerful Machine Learning (ML) models instead of offloading the computation tasks to more powerful devices. The ML boom has successfully penetrated these minuscule edge devices, which have started controlling important aspects of our lives (health and fitness, accessibility, financial transactions, etc.) and environment (smart homes, offices, cars, etc.). However, with increased capability comes increased risk of being attacked with malicious intent, especially because of the numerous vulnerabilities of the ubiquitous Bluetooth Low Energy (BLE) links between these IoT devices and the smartphone apps that control them.