Preserving privacy of online digital physiological signals using blind and reversible steganography

Bio-signal data sharing security through watermarking: a technical survey

Due to smart healthcare systems highly connected information and communications technologies, sensitive medical information and records are easily transmitted over the networks. However, stealing of healthcare data is increasing crime every day to greatly impact on financial loss. In order to this, researchers are developing various cost-effective bio-signal based data hiding techniques for smart healthcare applications. In this paper, we first introduce various aspects of data hiding along with major properties, generic embedding and extraction process, and recent applications. This survey provides a comprehensive survey on data hiding techniques, and their new trends for solving new challenges in real-world applications. Then, we survey the various notable bio-signal based data hiding techniques. The summary of some notable techniques in terms of their objective, type of data hiding, methodology and database used, performance metrics, important features, and limitations are also presented in tabular form. At the end, we discuss the major issues and research directions to explore the promising areas for future research.

Differential Watermarking of Multilead ECG Baseline

Digital watermarking has been widely recognized as an effective tool for embedment of auxiliary data in the host record. This paper presents a new method of watermarking using lead-to-lead difference of values in the baseline of the host electrocardiogram. The method starts with delineation of the baseline and uses Kirchoff voltage law or interpolation to predict any selected lead from the remaining ones. Next, the difference between the predicted and actual value is considered as noise and subjects to measurement of level and distribution in the time frame of baseline. The watermark with patient data or results of accompanying measurements is coded accordingly to mimic the noise. Replacement of the baseline noise with the watermark data ends the process. With 12-lead CSE files and respective reference borders of PQ and TP segments, the capacity of watermark achieved 3875 bits per second, while the diagnostic value of the ECG remains untouched.

QR code based patient data protection in ECG steganography

Connected health enables patient centric interventions resulting in better healthcare and hence better living. In order to accomplish this, bio-signals, medical and diagnosis information are shared and accessed by multiple actors and it is important to protect the privacy of patient data. Steganography is widely used to protect patient data by hiding it in the medical information. Current work investigates ECG steganography using Discrete Wavelet Transform (DWT) and Quick Response (QR) code. Steganography deteriorates the ECG signal and it is important to minimize this deterioration to preserve diagnosability. 1D ECG signal is converted to 2D ECG image and decomposed into sub-bands by subjecting it to DWT. The novelty of the proposed approach lies in converting the patient data into QR code and using it as watermark in ECG steganography. The QR code is embedded in the 2D image using additive quantization scheme. The performance of proposed method is measured using Peak Signal to Noise Ratio, Percentage Residual Difference and Kullback-Leibler distance. These metrics are used as a measure of imperceptibility while the data loss during retrieval is measured by Bit Retrieval Rate. The proposed method is demonstrated on normal ECG signals obtained from MIT-BIH database for different QR code versions. Metrics reveal that imperceptibility decreased for increasing patient data size and increasing scaling factors. Metrics were independent of the sub-band and the proposed method allows reliable patient data protection with full retrieval ability.

Optimizing Wavelet ECG Watermarking to Maintain Measurement Performance According to Industrial Standard

Watermarking is currently investigated as an efficient and safe method of embedding additional patient or environment-related data into the electrocardiogram. This paper presents experimental work on the assessment of the loss of ECG (electrocardiogram signal) diagnostic quality from the industrial standard EN60601-2-25:2015 point of view. We implemented an original time-frequency watermarking technique with an adaptive beat-to-beat lead-independent data container design. We tested six wavelets, six coding bit depth values (including the automatic noise-dependent one) and two types of watermark content to find the conditions that are necessary for watermarked ECG to maintain the compliance with International Electrotechnical Commission (IEC) requirements for interpretation performance. Unlike other authors, we did not assess the differences of signal values, but errors in ECG wave delineation results. The results of a total of 7300 original and watermarked 10 s ECGs were statistically processed to reveal possible interpretation quality degradation due to watermarking. Finally we found (1) the Symlet of 11-th order as the best of the wavelets that were tested; (2) the important role of ECG wave delineation and noise tracking procedures; (3) the high influence of the watermark-to-noise similarity of amplitude and values distribution and (4) the stability of the watermarking capacity for different heart rates in atrial rhythms.

Multiuser communication scheme based on binary phase-shift keying and chaos for telemedicine

BACKGROUND AND OBJECTIVES

Currently, telemedicine is levered upon the improvement in communication network technology such as Body Area Sensor Networks (BASN) to provided biomedicine solutions. Nevertheless, information security is an important issue since biomedical data is exchanged through insecure channels, which exposes private information that can be intercepted by malicious intruder. Therefore, secure communication protocols for multiuser networks in telemedicine applications are a big challenge. Recent chaos-based encryption works have been conducted in the area of medical secure communications with high security capabilities. However, none of them has considered multiuser network, which is used in several e-health applications. Up to our knowledge, the proposed protocol is the first attempt to consider this service in secure telemedicine. In this paper, we propose a novel scheme based on binary phase-shift key (BPSK) and chaos to provide information security at biosignals in a multiuser network system transmitting data over single channel.

METHODS

The proposed scheme uses the two-dimensional Hénon map with enhance pseudorandom sequences and CDMA technique to achieve multiuser encryption process and transmit data over a single channel. We use biosignals such as electrocardiograms (ECG) and blood pressure (PB) signals from PhisioBank ATM data base for simulation results at MatLab software. We evaluate the security and performance by determining the secret key space, secret key sensitivity, resistance against noise attack with quality analysis by using BER, MSE, and PSNR, encryption-decryption time, and throughput.

RESULTS

In simulations tests, biosignals of ECG and BP in a BANS network are encrypted and transmitted over shared wireless channels and just authorized medical personal can retrieve such information with corresponding secret key from the cryptogram, that appears as noise to any intruder. The proposed multiuser scheme support high noise and interference attacks efficiently in contrast with classic chaos-based encryption works for telemedicine, where some scenarios are simulated with very low BER, very low MSE, and high PSNR between plain biosignals and recovered biosignals when high AWGN noise is added to encrypted-transmitted signal. In addition, the encryption process presents enough key space and high sensitivity at secret key. A comparative analysis of proposed method and recent existing works was also presented.

CONCLUSIONS

Patients can be monitored and diagnosed opportunely remotely and all their medical information is transmitted securely to the correct specialist. Also, it is possible to transmit several electrophysiological signals in a single channel in a secure multiuser network at low cost optimizing the use of available bandwidth for telemedicine applications.