A Simple Chaos-Based Compressed Sensing with Encryption Scheme for Wearable IoT Devices
Chatchai Wannaboon, Patinya Ketthong · 2024
As an advancement of Internet-of-Thing (IoT) technology, wearable devices have become increasingly prevalent. However, ensuring the safety of the data and managing power consumption are crucial issue. This paper presents an integration of compressed sensing and encryption scheme for wearable IoT devices. The advantages of compressed sensing (CS) and chaotic system are integrated, i.e., reducing data transmission and storage requirements and concurrently enhancing the security and randomness of the encryption process. A 1-dimensional signum-based piecewise-linear chaotic map is utilized as a source of random sensing and robust key generation for the encryption. While the sparse measurement matrix effectively reduces the dimensionality of the data. The security and compressive capability are demonstrated through FitBit Fitness Tracker dataset, in terms of compression ratio, reconstruction quality, statistical analysis and security analysis. The results show that the scheme can achieve high compression and encryption efficiency, while facilitating transmission band-width without compromising quality of the information. The proposed system ensures minimal computational overhead and enable energy-saving feature that can be easily implemented to various types of wearable technologies.