Fortifying Patient Data Security in the Digital Era: A Two-Layer Approach with Data Hiding and Electrocardiogram

Authors

DOI:

https://doi.org/10.4108/eetsis.5644

Keywords:

ECG, data embedding, RDH, PSNR

Abstract

In an era dominated by digital technology, the imperative of securing patient data cannot be overstated. The deployment of advanced protective measures, including encryption, firewalls, and robust authentication protocols, is an absolute necessity when it comes to preserving the confidentiality and integrity of sensitive patient information. Furthermore, the establishment of stringent access controls serves as a fundamental safeguard, ensuring that only authorized personnel are granted access to this invaluable data. An innovative development in the realm of patient data protection is the utilization of ElectroCardioGram (ECG) as a unique identifier for individuals. In the context of this study, ECG data is ingeniously embedded within cover images using a technique known as Reversible Data Hiding (RDH). RDH offers a distinctive advantage by ensuring that the original image can be fully restored without loss of data after extraction. This achievement is made possible through the application of inventive pixel interpolation and histogram shifting algorithms. Crucially, the study's simulations, conducted across a diverse array of images, underscore the enhanced embedding capacity of the RDH technique while maintaining a commendable balance in terms of the Peak Signal to Noise Ratio (PSNR) and boundary map. This empirical evidence corroborates the efficacy of the approach and its potential to provide an advanced level of security for patient data in the digital landscape.

References

Siraj, Muhammed, Mohd Izuan Hafez Ninggal, Nur Izura Udzir, Muhammad Daniel Hafiz Abdullah, and Aziah Asmawi. "Smart-Contract Privacy Preservation Mechanism." EAI Endorsed Transactions on Scalable Information Systems 10, no. 6 (2023).

Gupta, Manish, and Rajendra Kumar Dwivedi. "Fortified MapReduce Layer: Elevating Security and Privacy in Big Data." EAI Endorsed Transactions on Scalable Information Systems 10, no. 6 (2023).

Al-Jubori, Hussein N., and Izzat Al-Darraji. "Tools and Process of Defect Detection in Automated Manufacturing Systems." EAI Endorsed Transactions on Scalable Information Systems 10, no. 6 (2023).

Pattnaik, Lal Mohan, Pratik Kumar Swain, Suneeta Satpathy, and Aditya N. Panda. "Cloud DDoS Attack Detection Model with Data Fusion & Machine Learning Classifiers." EAI Endorsed Transactions on Scalable Information Systems 10, no. 6 (2023).

Saxena, Drishti, and Prabhat Patel. "Energy-efficient clustering and cooperative routing protocol for wireless body area networks (WBAN)." Sādhanā 48, no. 2 (2023): 71.

Parveen, Nikhat, Manisha Gupta, Shirisha Kasireddy, Md Shamsul Haque Ansari, and Mohammad Nadeem Ahmed. "ECG based one-dimensional residual deep convolutional auto-encoder model for heart disease classification." Multimedia Tools and Applications (2024): 1-27.

Gupta, Praveen Kumar, and Vinay Avasthi. "Person identification using electrocardiogram and deep long short term memory." International Journal of Information Technology 15, no. 3 (2023): 1709-1717.

Shiu, Chih-Wei, Yu-Chi Chen, and Wien Hong. "Encrypted image-based reversible data hiding with public key cryptography from difference expansion." Signal Processing: Image Communication 39 (2015): 226-233.

Rakhra, Manik, Rajan Kumar, and Himdweep Walia. "A Review on Data hiding using Steganography and Cryptography." In 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 1-4. IEEE, 2021.

Kumar, Sanjay, Anjana Gupta, and Gurjit Singh Walia. "Reversible data hiding: A contemporary survey of state-of-the-art, opportunities and challenges." Applied Intelligence (2022): 1-34.

Gao, Guangyong, Shikun Tong, Zhihua Xia, Bin Wu, Liya Xu, and Zhiqiang Zhao. "Reversible data hiding with automatic contrast enhancement for medical images." Signal Processing 178 (2021): 107817.

Wang, Weiqing. "A reversible data hiding algorithm based on bidirectional difference expansion." Multimedia Tools and Applications 79, no. 9 (2020): 5965-5988.

Wu, Hao-Tian, Xin Cao, Ruoyan Jia, and Yiu-Ming Cheung. "Reversible data hiding with brightness preserving contrast enhancement by two-dimensional histogram modification." IEEE Transactions on Circuits and Systems for Video Technology 32, no. 11 (2022): 7605-7617.

Hou, Jiacheng, Bo Ou, Huawei Tian, and Zheng Qin. "Reversible data hiding based on multiple histograms modification and deep neural networks." Signal Processing: Image Communication 92 (2021): 116118.

Chang, Qi, Xiaolong Li, and Yao Zhao. "Reversible data hiding for color images based on adaptive three-dimensional histogram modification." IEEE Transactions on Circuits and Systems for Video Technology 32, no. 9 (2022): 5725-5735.

He, Wenguang, Gangqiang Xiong, and Yaomin Wang. "Reversible data hiding based on adaptive multiple histograms modification." IEEE Transactions on Information Forensics and Security 16 (2021): 3000-3012.

Jhong, Chun-Liang, and Hsin-Lung Wu. "Grayscale-invariant reversible data hiding based on multiple histograms modification." IEEE Transactions on Circuits and Systems for Video Technology 32, no. 9 (2022): 5888-5901.

Shaik, Ahmad, and V. Thanikaiselvan. "Comparative analysis of integer wavelet transforms in reversible data hiding using threshold based histogram modification." Journal of King Saud University-Computer and Information Sciences 33, no. 7 (2021): 878-889.

Khan A. Kamran, A. Malik, A high capacity reversible watermarking approach for authenticating images: exploiting down-sampling, histogram processing,

and block selection, Inf. Sci. 256 (2014) 162–183

J.S. Pan, C.N. Yang, C.C. Lin, Z.H. Wang, C.C. Chang, M.L. Li, et al., Multidimensional and multi-level histogram-shifting-imitated reversible data hiding scheme, Adv. Intell. Syst. Appl. 2 (2013) 149–158. Springer, Berlin Heidelberg.

W. Tai, C. Yeh, C. Chang, Reversible data hiding based on histogram modification of pixel differences, IEEE Trans. Circuits Syst. Video Technol. 19(6) (2009) 906–910.

C.C. Lin, W.L. Tai, C.C. Chang, Multilevel reversible data hiding based on histogram modification of difference images, Pattern Recogn. 41 (12) (2008)

–3591.

Hu, Runwen, and Shijun Xiang. "CNN prediction based reversible data hiding." IEEE Signal Processing Letters 28 (2021): 464-468.

Abadi MAM, Danyali H, Helfroush MS (2010) Reversible watermarking based on interpolation error histogram shifting. 5th International Symposium on Telecommunications (IST), Kish Island, Iran, p 840–845.

D.M. Thodi, J.J. Rodriguez, Prediction-error based reversible watermarking, in: International Conference on Image Processing, 2004, pp. 1549–1552.

Hassan, Fatuma Saeid, and Adnan Gutub. "Novel embedding secrecy within images utilizing an improved interpolation-based reversible data hiding scheme." Journal of King Saud University-Computer and Information Sciences 34, no. 5 (2022): 2017-2030.

Ma, Kede, Weiming Zhang, Xianfeng Zhao, Nenghai Yu, and Fenghua Li. "Reversible data hiding in encrypted images by reserving room before encryption." IEEE Transactions on information forensics and security 8, no. 3 (2013): 553-562.

Sah, Basant, and Vijay Kumar Jha. "Reversible data hiding technique using novel interpolation technique and discrete cosine transform." International Journal of Integrated Engineering 11, no. 1 (2019).

Tripathi, Abhinandan, and Jay Prakash. "Blockchain Enabled Interpolation Based Reversible Data Hiding Mechanism for Protecting Records." EAI Endorsed Transactions on Scalable Information Systems (2023):

Mohammad, Ahmad A. "A high quality interpolation-based reversible data hiding technique using dual images." Multimedia Tools and Applications 82, no. 24 (2023): 36713-36737.

Punia, Riya, Aruna Malik, and Samayveer Singh. "Innovative image interpolation based reversible data hiding for secure communication." Discover Internet of Things 3, no. 1 (2023): 22.

H. Jie, L. Tianrui, Reversible steganography using extended image interpolation technique, Comput. Electr. Eng. (2015), http://dx.doi.org/10.1016/

j.compeleceng.2015.04.01.

Wang, Xuan, Wenjie Cai, and Mingjie Wang. "A novel approach for biometric recognition based on ECG feature vectors." Biomedical Signal Processing and Control 86 (2023): 104922.

Hazratifard, Mehdi, Vibhav Agrawal, Fayez Gebali, Haytham Elmiligi, and Mohammad Mamun. "Ensemble Siamese Network (ESN) Using ECG Signals for Human Authentication in Smart Healthcare System." Sensors 23, no. 10 (2023): 4727.

Islam, Md Saiful, Naif Alajlan, Yakoub Bazi, and Haikel S. Hichri. "HBS: a novel biometric feature based on heartbeat morphology." IEEE transactions on Information Technology in Biomedicine 16, no. 3 (2012): 445-453.

Islam, Md Saiful, and Naif Alajlan. "Biometric template extraction from a heartbeat signal captured from fingers." Multimedia Tools and Applications 76 (2017): 12709-12733.

G. B. Moody and R. G. Mark, “The impact of the MIT-BIH arrhythmia database,” IEEE Engineering in Medicine and Biology Magazine, vol. 20, no. 3, pp. 45–50, 2001.

Islam, Md Saiful, Haikel Alhichri, Yakoub Bazi, Nassim Ammour, Naif Alajlan, and Rami M. Jomaa. "Heartprint: A Dataset of Multisession ECG Signal with Long Interval Captured from Fingers for Biometric Recognition." Data 7, no. 10 (2022): 141.

https://archive.physionet.org/physiobank/database/ecgiddb/

M. Bassiouni, W. Khaleefa, E. ElDahshan, and A.-B. M. Salem, “A machine learning technique for person identification using ECG signals,” Journal of Applied Physics, vol. 1, pp. 37–41, 2016.

X. Tang and L. Shu, “Classification of electrocardiogram signals with RS and quantum neural networks,” International Journal of Multimedia and Ubiquitous Engineering, vol. 9, no. 2, pp. 363–372,2014.

Q. Zhang, D. Zhou, and X. Zeng, “HeartID: a multiresolution convolutional neural network for ECG-based biometric human identification in smart health applications,” IEEE Access, vol. 5, pp. 11 805–11 816, 2017.

Abdeldayem, Sara S., and Thirimachos Bourlai. "A novel approach for ECG-based human identification using spectral correlation and deep learning." IEEE Transactions on Biometrics, Behavior, and Identity Science 2, no. 1 (2019): 1-14.

Zhao, Zhidong, Yefei Zhang, Yanjun Deng, and Xiaohong Zhang. "ECG authentication system design incorporating a convolutional neural network and generalized S-Transformation." Computers in biology and medicine 102 (2018): 168-179.

AlDuwaile, Dalal A., and Md Saiful Islam. "Using convolutional neural network and a single heartbeat for ECG biometric recognition." Entropy 23, no. 6 (2021): 733.

Downloads

Published

15-07-2024

How to Cite

1.
Gupta P, Prasad A. Fortifying Patient Data Security in the Digital Era: A Two-Layer Approach with Data Hiding and Electrocardiogram. EAI Endorsed Scal Inf Syst [Internet]. 2024 Jul. 15 [cited 2024 Jul. 26];11. Available from: https://publications.eai.eu/index.php/sis/article/view/5644

Issue

Section

Research articles