ENHANCING MEDICAL DATA SECURITY IN E-HEALTH SYSTEMS USING BIOMETRIC-BASED WATERMARKING
Ziadeddine MAKHLOUF
University of Echahid Cheikh Larbi Tebessi, Tebessa, LAboratory of Mathematics, Informatics and Systems (LAMIS) (Algeria)
https://orcid.org/0009-0000-9207-5277
Abdallah MERAOUMIA
University of Echahid Cheikh Larbi Tebessi, Tebessa, Laboratory of Mathematics, Informatics and Systems (LAMIS) (Algeria)
Laimeche LAKHDAR
lakhdar.laimeche@univ-tebessa.dz(Algeria)
https://orcid.org/0000-0002-9473-2637
Mohamed Yassine HAOUAM
University of Echahid Cheikh Larbi Tebessi, Tebessa, Laboratory of Mathematics, Informatics and Systems (LAMIS) (Algeria)
Abstract
In the field of Electronic Health (e-Health), Electronic Health Records (EHR) are transmitted between health professionals using e-Health systems for cooperative medical practice, medical monitoring, telemedical expertise, and telemedical imaging. Medical images are a crucial component of EHR and are used in various aspects of telemedicine systems such as expertise, consultation, teaching, and research. However, protecting the authenticity and copyrights of medical images is essential to prevent duplication, modification, or unauthorized distribution. This paper proposes a robust medical image copyright protection method that uses patient palm-print template as watermark and Lorenz chaotic map for template concealing and selecting the appropriate embedding positions in medical images. The novelty of the method lies in optimizing the expected number of modifications per pixel of the medical images after being watermarked. Experimental results indicate that this approach has a high performance with a genuine accept rate of 99.86% and can withstand various image processing attacks, including Gaussian noise, compression, and image rotations, while ensuring personal data security during telemedicine data exchange.
Keywords:
Watermarking, Biometric system, Chaotic systems, Medical imaging, TelemedicineReferences
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Bendib, I., Meraoumia, A., Haouam, M. Y., and Laimeche, L. (2022). A New Cancelable Deep Biometric Feature Using Chaotic Maps, Pattern Recognition and Image Analysis, 32 (1), https://doi:10.1134/S1054661821040052
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Cedillo-Hernandez, M., Cedillo-Hernandez, A., Nakano-Miyatake, M., Perez-Meana, H. (2020). Improving the management of medical imaging by using robust and secure dual watermarking, Biomedical Signal Processing Control, 56, https://doi.org/10.1016/j.bspc.2019.101695.
Cruz-Hernández, C., Abundiz-Pérez, F.,López-Gutiérrez, R.M. (2016). Implementation of an improved chaotic encryption algorithm for real-time embedded systems by using a 32-bit microcontroller, Microprocessors and Microsystems,45, 297-309, https://doi.org/10.1016/j.micpro.2016.06.004.
Fares, K., Khaldi, A., Redouane, K., Salah, E. (2021), DCT & DWT based watermarking scheme for medical information security, Biomedical Signal Processing Control, https://doi.org/10.1016/j.micpro.2021.104134.
Ghouzali, S., Nafea, O., Wadood, A., Hussain, M. (2021). Cancelable Multimodal Biometrics Based on Chaotic Maps. Applied Sciences. 11, 8573. https://doi.org/10.3390/app11188573
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Jain, J., Jain, A., Srivastava, S.K., Verma, C., Raboaca, M.S., Illés, Z. (2022). Improved Security of E-Healthcare Images Using Hybridized Robust Zero-Watermarking and Hyper-Chaotic System along with RSA. Mathematics, 10, 1071. https://doi.org/10.3390/math10071071.
Joshi, M., Joshi, K.P. & Finin T. (2018). Attribute Based Encryption for Secure Access to Cloud Based EHR Systems, Proceedings of the IEEE CLOUD Conference, 2018, San Francisco.
Kang G. & Kim Y.G. (2022). Secure Collaborative Platform for Health Care Research in an Open Environment: Perspective on Accountability in Access Control, Journal Medical Internet Research, https://doi: 10.2196/37978 .
Krishnan, C. & Lalitha, T. (2020). Securing Healthcare Data using Attribute based Encryption Techniques in Cloud Environment, European Journal of Molecular & Clinical Medicine, 7 (11), 6271-6280.
Laimeche, L., Meraoumia, A., Bendjenna H. (2020). Enhancing LSB embedding schemes using chaotic maps systems. Neural Computing & Applications, 32, 16605–16623, https://doi:10.1007/s00521-019-04523-z.
Laimeche, L., Merouani, F. H., Smain, M. (2016). A new binary similarity metric for two LSB steganalysis, International Conference on Information Technology for Organizations Development (IT4OD), Fez, Morocco, 1-7.
Mohan P.H. (2020), Secure medical data transmission using a fusion of bit mask oriented genetic algorithm, encryption and steganography, Future Generation Computer System, 111, 213–225, https://doi.org/10.1016/j.future.2020.04.034.
Pallaw, V.K., Singh, K.U., Kumar, A., Singh, T., Swarup, C. & Goswami, A. (2023). A Robust Medical Image Watermarking Scheme Based on Nature-Inspired Optimization for Telemedicine Applications. Electronics, 12, 334. https://doi.org/10.3390/electronics12020334.
Roslan, R. & Jamil, N. (2012). Texture feature extraction using 2-D Gabor Filters, International Symposium on Computer Applications and Industrial Electronics (ISCAIE), Kota Kinabalu, Malaysia, , pp. 173-178.
Sermanet, P., Chintala, S., & LeCun, Y. (2009). Gabor feature extraction for automatic speech recognition, IEEE Transactions on Audio, Speech, and Language Processing, 17(2), 214-225.
Tertulino, R., Antunes, N. & Morais, H. (2022). Privacy in electronic health records: a systematic mapping study, Journal of Public Health, https://doi.org/10.1007/s10389-022-01795-z.
Tsou C., Robinson S., Boyd J., Jamieson A., Blakeman R., Yeung J., McDonnell J., Waters S., Bosich K., Hendrie D. (2021). Effectiveness of Telehealth in Rural and Remote Emergency Departments: Systematic Review. Journal of Medical Internet Research, 23(11), https://doi: 10.2196/30632.
Vaidya, S.P. (2022). Fingerprint-based robust medical image watermarking in hybrid transform. The Visual Computer, https://doi.org/10.1007/s00371-022-02406-4.
Wadood, A., Nafea,O. Ghouzali,S.(2020). Combining Watermarking and Hyper-Chaotic Map to Enhance the Security of Stored Biometric Templates, The Computer Journal, 63(3), 479-493, https://doi.org/10.1093/comjnl/bxz047
Ye, C., Chen, C. (2022). Secure medical image sharing for smart healthcare system based on cellular neural network. Complex Intelligent Systems, https://doi.org/10.1007/s40747-022-00881-9.
.Zulfiqar, A., Muhammad, I., Mansour, A., Tanveer, Z., Muhammad, S. (2018). A zero-watermarking algorithm for privacy protection in biomedical signals, Future Generation Computer Systems, 82, 290-303, https://doi.org/10.1016/j.future.2017.12.007.
Aparna, P., Kishore, P.V.V. (2019). Biometric-based efficient medical image watermarking in e-healthcare application, IET Image Processing, 13(3), 421–428, https://doi.org/10.1049/iet-ipr.2018.5288
Bendib, I., Meraoumia, A., Haouam, M. Y., and Laimeche, L. (2022). A New Cancelable Deep Biometric Feature Using Chaotic Maps, Pattern Recognition and Image Analysis, 32 (1), https://doi:10.1134/S1054661821040052
Bervell, B. & Al-Samarraie, H. (2019). A comparative review of mobile health and electronic health utilization in sub-Saharan African countries. Social Science and Medicine, 232, 1-16. https://doi.org/10.1016/j.socscimed.2019.04.024.
Cedillo-Hernandez, M., Cedillo-Hernandez, A., Nakano-Miyatake, M., Perez-Meana, H. (2020). Improving the management of medical imaging by using robust and secure dual watermarking, Biomedical Signal Processing Control, 56, https://doi.org/10.1016/j.bspc.2019.101695.
Cruz-Hernández, C., Abundiz-Pérez, F.,López-Gutiérrez, R.M. (2016). Implementation of an improved chaotic encryption algorithm for real-time embedded systems by using a 32-bit microcontroller, Microprocessors and Microsystems,45, 297-309, https://doi.org/10.1016/j.micpro.2016.06.004.
Fares, K., Khaldi, A., Redouane, K., Salah, E. (2021), DCT & DWT based watermarking scheme for medical information security, Biomedical Signal Processing Control, https://doi.org/10.1016/j.micpro.2021.104134.
Ghouzali, S., Nafea, O., Wadood, A., Hussain, M. (2021). Cancelable Multimodal Biometrics Based on Chaotic Maps. Applied Sciences. 11, 8573. https://doi.org/10.3390/app11188573
Haouam, M.Y., Meraoumia, A., Laimeche, L., Bendib, I. (2021). S-DCTNet: Security-oriented biometric feature extraction technique. Multimedia Tools Applications 80, 36059–36091, https://doi.org/10.1007/s11042-021-10936-7.
Idoga, P. E., Agoyi, M. E., Coker-Farrell Y. & Ekeoma, O. L. (2016). Review of security issues in e-Healthcare and solutions, International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET, 118-121, https://doi: 10.1109/HONET.2016.7753433.
Jain, J., Jain, A., Srivastava, S.K., Verma, C., Raboaca, M.S., Illés, Z. (2022). Improved Security of E-Healthcare Images Using Hybridized Robust Zero-Watermarking and Hyper-Chaotic System along with RSA. Mathematics, 10, 1071. https://doi.org/10.3390/math10071071.
Joshi, M., Joshi, K.P. & Finin T. (2018). Attribute Based Encryption for Secure Access to Cloud Based EHR Systems, Proceedings of the IEEE CLOUD Conference, 2018, San Francisco.
Kang G. & Kim Y.G. (2022). Secure Collaborative Platform for Health Care Research in an Open Environment: Perspective on Accountability in Access Control, Journal Medical Internet Research, https://doi: 10.2196/37978 .
Krishnan, C. & Lalitha, T. (2020). Securing Healthcare Data using Attribute based Encryption Techniques in Cloud Environment, European Journal of Molecular & Clinical Medicine, 7 (11), 6271-6280.
Laimeche, L., Meraoumia, A., Bendjenna H. (2020). Enhancing LSB embedding schemes using chaotic maps systems. Neural Computing & Applications, 32, 16605–16623, https://doi:10.1007/s00521-019-04523-z.
Laimeche, L., Merouani, F. H., Smain, M. (2016). A new binary similarity metric for two LSB steganalysis, International Conference on Information Technology for Organizations Development (IT4OD), Fez, Morocco, 1-7.
Mohan P.H. (2020), Secure medical data transmission using a fusion of bit mask oriented genetic algorithm, encryption and steganography, Future Generation Computer System, 111, 213–225, https://doi.org/10.1016/j.future.2020.04.034.
Pallaw, V.K., Singh, K.U., Kumar, A., Singh, T., Swarup, C. & Goswami, A. (2023). A Robust Medical Image Watermarking Scheme Based on Nature-Inspired Optimization for Telemedicine Applications. Electronics, 12, 334. https://doi.org/10.3390/electronics12020334.
Roslan, R. & Jamil, N. (2012). Texture feature extraction using 2-D Gabor Filters, International Symposium on Computer Applications and Industrial Electronics (ISCAIE), Kota Kinabalu, Malaysia, , pp. 173-178.
Sermanet, P., Chintala, S., & LeCun, Y. (2009). Gabor feature extraction for automatic speech recognition, IEEE Transactions on Audio, Speech, and Language Processing, 17(2), 214-225.
Tertulino, R., Antunes, N. & Morais, H. (2022). Privacy in electronic health records: a systematic mapping study, Journal of Public Health, https://doi.org/10.1007/s10389-022-01795-z.
Tsou C., Robinson S., Boyd J., Jamieson A., Blakeman R., Yeung J., McDonnell J., Waters S., Bosich K., Hendrie D. (2021). Effectiveness of Telehealth in Rural and Remote Emergency Departments: Systematic Review. Journal of Medical Internet Research, 23(11), https://doi: 10.2196/30632.
Vaidya, S.P. (2022). Fingerprint-based robust medical image watermarking in hybrid transform. The Visual Computer, https://doi.org/10.1007/s00371-022-02406-4.
Wadood, A., Nafea,O. Ghouzali,S.(2020). Combining Watermarking and Hyper-Chaotic Map to Enhance the Security of Stored Biometric Templates, The Computer Journal, 63(3), 479-493, https://doi.org/10.1093/comjnl/bxz047
Ye, C., Chen, C. (2022). Secure medical image sharing for smart healthcare system based on cellular neural network. Complex Intelligent Systems, https://doi.org/10.1007/s40747-022-00881-9.
.Zulfiqar, A., Muhammad, I., Mansour, A., Tanveer, Z., Muhammad, S. (2018). A zero-watermarking algorithm for privacy protection in biomedical signals, Future Generation Computer Systems, 82, 290-303, https://doi.org/10.1016/j.future.2017.12.007.
MAKHLOUF, Z., MERAOUMIA , A. ., LAKHDAR, L., & HAOUAM , M. Y. . (2024). ENHANCING MEDICAL DATA SECURITY IN E-HEALTH SYSTEMS USING BIOMETRIC-BASED WATERMARKING. Applied Computer Science, 20(1), 28–55. https://doi.org/10.35784/acs-2024-03
Authors
Ziadeddine MAKHLOUFUniversity of Echahid Cheikh Larbi Tebessi, Tebessa, LAboratory of Mathematics, Informatics and Systems (LAMIS) Algeria
https://orcid.org/0009-0000-9207-5277
Authors
Abdallah MERAOUMIAUniversity of Echahid Cheikh Larbi Tebessi, Tebessa, Laboratory of Mathematics, Informatics and Systems (LAMIS) Algeria
Authors
Laimeche LAKHDARlakhdar.laimeche@univ-tebessa.dz
Algeria
https://orcid.org/0000-0002-9473-2637
Authors
Mohamed Yassine HAOUAMUniversity of Echahid Cheikh Larbi Tebessi, Tebessa, Laboratory of Mathematics, Informatics and Systems (LAMIS) Algeria
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