An Integrated Approach Using Chaotic Map & Sample Value Difference Method for Electrocardiogram Steganography and OFDM Based Secured Patient Information Transmission

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.

A morphologically robust chaotic map based approach to embed patient's confidential data securely in non-QRS regions of ECG signal

In e-healthcare paradigm, the physiological signals along with patient's personal information need to be transmitted to remote healthcare centres. Before sharing this sensitive information over the unsecured channel, it is prerequisite to protect it from unauthorised access. The proposed method explores ECG signal as the cover signal to hide patient's personal information without disturbing its diagnostic features. Chaotic maps are used to randomly select the embedding locations in the non-QRS region while excluding the sensitive QRS region of ECG train. Optimum Location Selection algorithm has been designed to select the embedding locations in non-QRS embedding region. The proposed algorithm is thoroughly examined and the distortion is measured in terms of statistical parameters and clinical measures such as PRD, PRDN, PRD1024, PSNR, SNR, MSE, MAE, KL-Divergence, WWPRD and WEDD. The robustness of the algorithm is verified using the parameters such as key space and key sensitivity. The implementation has been extensively tested on all the 48 records of the standard MIT-BIH Arrhythmia database, abnormal databases [CU-VT, BIDMC-CHF and PTB (leads I, II and III)] and self-recorded data of 20 subjects. The algorithm yields average PRD, MSE, KL-Divergence, PSNR, WWPRD and WEDD of 4.7 × 10^-3, 1.13 × 10^-5, 1.29 × 10^-5, 50.28, 0.15 and 0.04 at an average maximum EC of 0.45(96876 bits) on MIT-BIH Arrhythmia database and 0.016, 3.38 × 10^-5, 1.8 × 10^-4, 46.03, 0.13 and 0.03 respectively at an average maximum EC of 0.47 (102571 bits) on self-recorded data which clearly reveals the competency of the proposed algorithm in comparison with the other state of the art ECG steganography approaches.

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.