Evaluation of Software PUF Based on Gyroscope

Abstract

The Physically Unclonable Function (PUF), which extracts a unique device identification based on variations in manufacturing processes, has recently attracted attention. IoT devices, including sensor monitors and wearables, have come into widespread use, and various kinds of devices have access to a range of services. Device authentication and management of key to encryption communication data are essential for a secure service. We can realize secure authentication based on device identification extracted by a PUF. For example, PUF is used as a key generator to avoid storing the encryption key in a device. However, existing PUFs require dedicated hardware or software (driver) to extract device identification. Thus, it may not be possible to apply existing PUFs to IoT devices in a situation where there are a variety of devices and many device manufacturers. We can use characteristic values of existing sensors in an IoT device as an alternative to PUF. In this paper, we expand an existing software PUF based to support characteristic values extract from a gyroscope, and evaluate the entropy and robustness. We found that the same device identifier can be reliably extracted from a gyroscope even under conditions of high and low temperature, and low-pressure. No changes in the characteristic values of the gyroscope due to degradation with age were found over a wearing period exceeding than three years. The device identifier has up to 81.2 bits entropy with no error-correcting mechanism. It has up to 57.7 bits entropy when error-correction of one bit is applied to each characteristic value by a Fuzzy extractor.