Privacy Assured Recovery of Compressively Sensed ECG signals
This addresses privacy concerns in cloud-based ECG analysis for wearable IoT devices, though it is incremental as it builds on existing compressive sensing and encryption techniques.
The paper tackles the problem of securely outsourcing the recovery of compressively sensed ECG signals to the cloud while preserving privacy, achieving this by recovering an encrypted version of the signal that can be decrypted by the user with a key, and demonstrates the method using the MITBIH Arrhythmia Database with resistance to partial key exposure.
Cloud computing for storing data and running complex algorithms have been steadily increasing. As connected IoT devices such as wearable ECG recorders generally have less storage and computational capacity, acquired signals get sent to a remote center for storage and possible analysis on demand. Recently, compressive sensing (CS) has been used as secure, energy-efficient method of signal sampling in such recorders. In this paper, we propose a secure procedure to outsource the total recovery of CS measurement to the cloud and introduce a privacy-assured signal recovery technique in the cloud. We present a fast, and lightweight encryption for secure CS recovery outsourcing that can be used in wearable devices, such as ECG Holter monitors. In the proposed technique, instead of full recovery of CS-compressed ECG signal in the cloud, to preserve privacy, an encrypted version of ECG signal is recovered by using a randomly bipolar permuted measurement matrix. The user with a key, decrypts the encrypted ECG from the cloud to obtain the original ECG signal. We demonstrate our proposed method using the ECG signals available in the MITBIH Arrhythmia Database. We also demonstrate the strength of the proposed method against partial exposure of the key.