Privacy Assured Recovery of Compressively Sensed ECG signals

TL;DR

This paper introduces a privacy-preserving method for recovering compressively sensed ECG signals in the cloud, using lightweight encryption and a permuted measurement matrix, suitable for wearable devices like Holter monitors.

Contribution

It proposes a novel secure recovery technique for compressively sensed signals that ensures privacy while enabling efficient cloud-based ECG signal reconstruction.

Findings

Effective privacy preservation against key exposure

Compatible with resource-constrained wearable devices

Validated on MITBIH ECG dataset

Abstract

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.