Steganography in arrhythmic electrocardiogram signal

Security and privacy of patient data is a vital requirement during exchange/storage of medical information over communication network. Steganography method hides patient data into a cover signal to prevent unauthenticated accesses during data transfer. This study evaluates the performance of ECG steganography to ensure secured transmission of patient data where an abnormal ECG signal is used as cover signal. The novelty of this work is to hide patient data into two dimensional matrix of an abnormal ECG signal using Discrete Wavelet Transform and Singular Value Decomposition based steganography method. A 2D ECG is constructed according to Tompkins QRS detection algorithm. The missed R peaks are computed using RR interval during 2D conversion. The abnormal ECG signals are obtained from the MIT-BIH arrhythmia database. Metrics such as Peak Signal to Noise Ratio, Percentage Residual Difference, Kullback-Leibler distance and Bit Error Rate are used to evaluate the performance of the proposed approach.

I. Introduction

Advances in medical devices enable ubiquitous monitoring of a patient's physiological parameters. The acquired medical information is tagged with patient's personal data and transmitted to the remote healthcare unit or care giver over internet. During such transmission security of patient data is an essential requirement in remote healthcare monitoring to avoid unauthenticated accesses. The U.S Department of Health and Human Services (DHHS) introduced a law for data security and privacy under the Health Insurance Portability and Accountability (HIPP A) 1996 [1]. Steganography is an art of hiding data inside another data. Information which hides the data is referred as cover signal and the data to be hidden is named as watermark. This method can be extended to ensure secured transmission of patient data in healthcare domain. Cover signal is one of the medical information such as Magnetic Resonance Imaging (MRI), Computerized Tomography (CT scan), Electrocardiogram (ECG) and Electro encephalogram (EEG). Patient's personal information such as name, age, location and other medical history are the data to be protected.