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A Survey on Healthcare Data: A Security Perspective

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Published:18 May 2021Publication History
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Abstract

With the remarkable development of internet technologies, the popularity of smart healthcare has regularly come to the fore. Smart healthcare uses advanced technologies to transform the traditional medical system in an all-round way, making healthcare more efficient, more convenient, and more personalized. Unfortunately, medical data security is a serious issue in the smart healthcare systems. It becomes a fundamental challenge that requires the development of efficient innovative strategies towards fulfilling the healthcare needs and supporting secure healthcare transfer and delivery. This article provides a comprehensive survey on state-of-the-art techniques for health data security and their new trends for solving challenges in real-world applications. We survey the various notable cryptography, biometrics, watermarking, and blockchain-based security techniques for healthcare applications. A comparative analysis is also performed to identify the contribution of reviewed techniques in terms of their objective, methodology, type of medical data, important features, and limitations. At the end, we discuss the open issues and research directions to explore the promising areas for future research.

References

  1. A. K. Singh, B. Kumar, G. Singh, and A. Mohan. 2017. Medical Image Watermarking: Techniques and Applications. Springer International Publishing.Google ScholarGoogle Scholar
  2. A. Anand and A. K. Singh. 2020. Watermarking techniques for medical data authentication: a survey. Multimed. Tools Appl. 2020.Google ScholarGoogle Scholar
  3. 2020. Greatest Cybersecurity Threats Facing Healthcare Networks in 2020. Retrieved from https://www.securitymagazine.com/articles/91751-greatest-cybersecurity-threats-facing-healthcare-networks-in-2020.Google ScholarGoogle Scholar
  4. A. Anand and A. K. Singh. 2020. An improved DWT-SVD domain watermarking for medical information security. Comput. Commun. 152 (2020), 72–80. DOI: 10.1016/j.comcom.2020.01.038Google ScholarGoogle ScholarCross RefCross Ref
  5. A. K. Singh, Z. Lv, S. Rho, S. K. Singh, X. Chang, and W. Puech. 2018. IEEE access special section editorial: Information security solutions for telemedicine applications. IEEE Access 6 (2018), 79005–79009. DOI: 10.1109/ACCESS.2018.2885256Google ScholarGoogle ScholarCross RefCross Ref
  6. A. Anand, A. K. Singh, Z. Lv, and G. Bhatnagar. 2020. Compression-then-encryption based secure watermarking technique for smart healthcare system. IEEE Multimed. (2020). DOI: 10.1109/MMUL.2020.2993269Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. F. Cao, H. K. Huang, and X. Q. Zhou. 2003. Medical image security in a HIPAA mandated PACS environment. Comput. Med. Imaging Graph. 27, 2–3 (2003), 185–196, DOI: 10.1016/S0895-6111(02)00073-3Google ScholarGoogle ScholarCross RefCross Ref
  8. M. Li, R. Poovendran, and S. Narayanan. 2005. Protecting patient privacy against unauthorized release of medical images in a group communication environment. Comput. Med. Imaging Graph. 29, 5 (2005), 367–383. DOI: 10.1016/j.compmedimag.2005.02.003Google ScholarGoogle ScholarCross RefCross Ref
  9. W. Burke, T. Oseni, A. Jolfaei, and I. Gondal. 2019. Cybersecurity indexes for ehealth. In Proceedings of the ACM International Australasian Computer Science Week Multiconference. DOI: 10.1145/3290688.3290721 Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. S. Tian, W. Yang, J. M. Le Grange, P. Wang, W. Huang, and Z. Ye. 2019. Smart healthcare: Making medical care more intelligent. Glob. Health J. 3, 3 (2019), 62–65. DOI: 10.1016/j.glohj.2019.07.001Google ScholarGoogle ScholarCross RefCross Ref
  11. P. Sundaravadivel, E. Kougianos, S. P. Mohanty, and M. K. Ganapathiraju. 2018. Everything you wanted to know about smart health care: Evaluating the different technologies and components of the internet of things for better health. IEEE Consum. Electron. Mag. 7, 1 (2018), 18–28. DOI: 10.1109/MCE.2017.2755378Google ScholarGoogle ScholarCross RefCross Ref
  12. M. Demchenko. 2020. Trends in healthcare 2020: Get ready for digital transformation. NCube. Retrieved from https://ncube.com/blog/trends-in-healthcare-2020-get-ready-for-digital-transformationGoogle ScholarGoogle Scholar
  13. A. K. Singh and C. Kumar. 2020. Encryption-then-compression-based copyright protection scheme for e-governance. IEEE IT Prof. 22, 2 (2020), 45–52. DOI: 10.1109/MITP.2019.2961898Google ScholarGoogle ScholarCross RefCross Ref
  14. A. Anand and A. K. Singh. 2020. Joint watermarking-encryption-ECC for patient record security in wavelet domain. IEEE Multimed. (2020). DOI: 10.1109/MMUL.2020.2985973Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. U. Rajendra Acharya, U. C. Niranjan, S. S. Iyengar, N. Kannathal, and L. C. Min. 2004. Simultaneous storage of patient information with medical images in the frequency domain. Comput. Meth. Prog. Biomed. 76, 1 (2004), 13–19. DOI: 10.1016/j.cmpb.2004.02.009Google ScholarGoogle ScholarCross RefCross Ref
  16. S. Thakur, A. K. Singh, S. Ghrera, and M. Dave. 2019. Watermarking techniques and its applications in tele-health: A technical survey. Cryptogr. Inf. Secur. (2019). DOI: 10.1201/9780429435461-17Google ScholarGoogle Scholar
  17. D. Gupta, B. Perez, G. M. Agrawal, and D. P. Gupta. 2020. Handbook of Computer Networks and Cyber Security: Principles and Paradigms. Springer.Google ScholarGoogle Scholar
  18. A. M. Qadir and N. Varol. 2019. A review paper on cryptography. In Proceedings of the 7th International Symposium on Digital Forensics Security. DOI: 10.1109/ISDFS.2019.8757514Google ScholarGoogle Scholar
  19. A. Al-Haj, G. Abandah, and N. Hussein. 2015. Crypto-based algorithms for secured medical image transmission. IET Inf. Secur. 9, 6 (2015), 365–373. DOI: 10.1049/iet-ifs.2014.0245Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Y. Zhou, K. Panetta, and S. Agaian. 2009. A lossless encryption method for medical images using edge maps. In Proceedings of the 31st International Conference of the IEEE Engineering in Medicine and Biology Society. 3707–3710. DOI: 10.1109/IEMBS.2009.5334799Google ScholarGoogle Scholar
  21. J. N. B. Salameh. 2019. A new approach for securing medical images and patient's information by a new approach for securing medical imag es and patient’s information by using a hybrid system. Int. J. Comput. Sci. Netw. Secur. 19, 4 (2019), 28–39.Google ScholarGoogle Scholar
  22. S. Arunkumar, V. Subramaniyaswamy, V. Vijayakumar, N. Chilamkurti, and R. Logesh. 2019. SVD-based robust image steganographic scheme using RIWT and DCT for secure transmission of medical images. Meas. J. Int. Meas. Confed. 139 (2019), 426–437. DOI: 10.1016/j.measurement.2019.02.069Google ScholarGoogle ScholarCross RefCross Ref
  23. C. C. Chang, Y. P. Hsieh, and C. H. Lin. 2008. Sharing secrets in stego images with authentication. Pattern Recog. 41, 10 (2008), 3130–3137. DOI: 10.1016/j.patcog.2008.04.006 Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. C. C. Wu, S. J. Kao, and M. S. Hwang. 2011. A high quality image sharing with steganography and adaptive authentication scheme. J. Syst. Softw. 84, 12 (2011), 2196–2207. DOI: 10.1016/j.jss.2011.06.021 Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. H. R. Kanan and B. Nazeri. 2014. A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm. Expert Syst. Appl. 41, 14 (2014), 6123–6130. DOI: 10.1016/j.eswa.2014.04.022Google ScholarGoogle ScholarCross RefCross Ref
  26. B. Vinoth, M. Ramaswami, and P. Swathika. 2017. Data security on patient monitoring for future healthcare application. Int. J. Comput. Appl 163, 6 (2017), 20–23. DOI: 10.5120/ijca2017913548Google ScholarGoogle Scholar
  27. S. Sujatha and R. Govindaraju. 2013. A secure crypto based ECG data communication using modified SPHIT and modified quasigroup encryption. Int. J. Comput. Appl. 78, 6 (2013), 27–33. DOI: 10.5120/13494-1217Google ScholarGoogle Scholar
  28. K. Shankar, M. Elhoseny, E. D. Chelvi, S. K. Lakshmanaprabu, and W. Wu. 2018. An efficient optimal key based chaos function for medical image security. IEEE Access 6 (2018), 77145–77154. DOI: 10.1109/ACCESS.2018.2874026Google ScholarGoogle ScholarCross RefCross Ref
  29. S. Toughi, M. H. Fathi, and Y. A. Sekhavat. 2017. An image encryption scheme based on elliptic curve pseudo random and advanced encryption system. Sig. Proc. 141 (2017), 217–227. DOI: 10.1016/j.sigpro.2017.06.010 Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. A. M. Vengadapurvaja, G. Nisha, R. Aarthy, and N. Sasikaladevi. 2017. An efficient homomorphic medical image encryption algorithm for cloud storage security. Procedia Comput. Sci. 115 (2017), 643–650. DOI: 10.1016/j.procs.2017.09.150 Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. K. Shankar and S. K. Lakshmanaprabu. 2018. Optimal key based homomorphic encryption for color image security aid of ant lion optimization algorithm. Int. J. Eng. Technol. 7, 1 (2018), 22–27. DOI: 10.14419/ijet.v7i1.9.9729Google ScholarGoogle Scholar
  32. R. Parvaz and M. Zarebnia. 2018. A combination chaotic system and application in color image encryption. Opt. Laser Technol. 101 (2018), 30–41. DOI: 10.1016/j.optlastec.2017.10.024Google ScholarGoogle ScholarCross RefCross Ref
  33. J. Sun, X. Zhu, C. Zhang, and Y. Fang. 2011. HCPP: Cryptography based secure EHR system for patient privacy and emergency healthcare. In Proceedings of the International Conference on Distributed Computer Systems. 373–382. DOI: 10.1109/ICDCS.2011.83 Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. M. M. Abd-Eldayem. 2013. A proposed security technique based on watermarking and encryption for digital imaging and communications in medicine. Egypt. Informatics J. 14, 1 (2013), 1–13. DOI: 10.1016/j.eij.2012.11.002Google ScholarGoogle ScholarCross RefCross Ref
  35. A. Sharma, A. K. Singh, and S. P. Ghrera. 2015. Secure hybrid robust watermarking technique for medical images. Procedia Comput. Sci. 70 (2015), 778–784. DOI: 10.1016/j.procs.2015.10.117Google ScholarGoogle ScholarCross RefCross Ref
  36. S. Nagamani and D. C. Nagaraju. 2018. A mobile cloud-based approach for secure m-health prediction application. Int. J. Innov. Eng. Manag. Res. 7, 12 (2018), 236–244. DOI: 10.22214/ijraset.2017.4212Google ScholarGoogle Scholar
  37. S. Chirakkarottu and S. Mathew. 2020. A novel encryption method for medical images using 2D Zaslavski map and DNA cryptography. SN Appl. Sci. 2, 1 (2020), 1–10. DOI: 10.1007/s42452-019-1685-8Google ScholarGoogle ScholarCross RefCross Ref
  38. M. Dridi, B. Bouallegue, and A. Mtibaa. 2014. Crypto-compression of medical image based on DCT and chaotic system. In Proceedings of the Global Summit on Computer & Information Technology (GSCIT'14). DOI: 10.1109/GSCIT.2014.6970113Google ScholarGoogle Scholar
  39. S. Thakur, A. K. Singh, B. Kumar, and S. P. Ghrera. 2020. Improved DWT-SVD-based medical image watermarking through hamming code and chaotic encryption.VLSI, Commun. Sig. Proc. Lect. Notes Electr. Eng., 587 (2020), 897–905.Google ScholarGoogle ScholarCross RefCross Ref
  40. Z. Yue et al. 2020. Privacy-preserving time series medical images analysis using a hybrid deep learning framework. ACM Trans. Internet Technol. (2020). DOI: 10.1145/3383779Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. S. Ji, W. Xu, M. Yang, and K. Yu. 2013. 3D Convolutional neural networks for human action recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35, 1 (2013), 221–231. DOI: 10.1109/TPAMI.2012.59 Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. H. Yang et al. 2019. Asymmetric 3D convolutional neural networks for action recognition. Pattern Recog. 85 (2019), 1–12. DOI: 10.1016/j.patcog.2018.07.028Google ScholarGoogle ScholarCross RefCross Ref
  43. A. H. Y. Zhu, Z. Lan, and S. Newsam. 2018. Hidden two-stream convolutional networks for action recognition. In Proceedings of the Asian Conference on Computer Vision. 363–378. DOI: doi.org/10.1007/978-3-030-20893-6Google ScholarGoogle Scholar
  44. The National Library of Medicine presents MedPix. Retrieved from https://www.nlm.nih.gov/news/medpix_image_database.html.Google ScholarGoogle Scholar
  45. N. H. Hussein, A. Khalid, and K. Khanfar. 2016. A survey of cryptography cloud storage techniques. Int. J. Comput. Sci. Mob. Comput. 5, 2 (2016), 186–191.Google ScholarGoogle Scholar
  46. A. Kumar and K. Pooja. 2010. Steganography—A data hiding technique. Int. J. Comput. Appl. 9, 7 (2010), 19–23, DOI: 10.5120/1398-1887Google ScholarGoogle ScholarCross RefCross Ref
  47. A. K. Jain, P. Flynn, and A. Ross. 2008. Handbook of Biometrics. Springer Science & Business Media: Berlin, Germany. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. W. Yang, S. Wang, J. Hu, G. Zheng, and C. Valli. 2019. Security and accuracy of fingerprint-based biometrics: A review. Symmetry (Basel). 11, 2 (2019). DOI: 10.3390/sym11020141Google ScholarGoogle Scholar
  49. A. K. Jain, A. Ross, and S. Prabhakar. 2004. An introduction to biometric recognition. IEEE Trans. Circ. Syst. Video Technol. 14, 1 (2004), 4–20. DOI: 10.1109/TCSVT.2003.818349 Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. K. A. Shakil, F. J. Zareen, M. Alam, and S. Jabin. 2020. BAMHealthCloud: A biometric authentication and data management system for healthcare data in cloud. J. King Saud Univ.—Comput. Inf. Sci. 32, 1 (2020), 57–64. DOI: 10.1016/j.jksuci.2017.07.001Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. H. Silva, A. Lourenço, A. Fred, and J. Filipe. 2011. Clinical data privacy and customization via biometrics based on ECG signals. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), 7058 LNCS, 121–132. DOI: 10.1007/978-3-642-25364-5_12Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. S. Jahan, M. Chowdhury, and R. Islam. 2019. Robust user authentication model for securing electronic healthcare system using fingerprint biometrics. Int. J. Comput. Appl. 41, 3 (2019), 233–242. DOI: 10.1080/1206212X.2018.1437651Google ScholarGoogle ScholarCross RefCross Ref
  53. A. I. Awad and K. Baba. 2012. Evaluation of a fingerprint identification algorithm with SIFT features. In Proceedings of the IIAI International Congress on Advanced Applied Informatics. 129–132. DOI: 10.1109/IIAI-AAI.2012.34 Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. R. Zhou, D. Zhong, and J. Han. 2013. Fingerprint identification using SIFT-based minutia descriptors and improved all descriptor-pair matching. Sensors (Switzerland) 13, 3 (2013), 3142–3156. DOI: 10.3390/s130303142Google ScholarGoogle ScholarCross RefCross Ref
  55. L. Liu and T. Cao. 2012. The research and design of an efficient verification system based on biometrics. In Proceedings of the International Conference on Computer Science and Electrical Engineering. 707–710. DOI: 10.1109/ICCSEE.2012.435 Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. U. Park, S. Pankanti, and A. K. Jain. 2008. Fingerprint verification using SIFT features. Biomet. Technol. Hum. Identif. V 6944 (2008), 69440K. DOI: 10.1117/12.778804Google ScholarGoogle Scholar
  57. D. A. Ramli, M. Y. Hooi, and K. J. Chee. 2016. Development of heartbeat detection kit for biometric authentication system. Procedia Comput. Sci. 96 (2016), 305–314. DOI: 10.1016/j.procs.2016.08.143 Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. J. N. Lee, S. B. Pan, and K. C. Kwak. 2019. Individual identification based on cascaded PCANet from ECG signal. In Proceedings of the International Conference on Electronics, Information, and Communication. 1–4. DOI: 10.23919/ELINFOCOM.2019.8706366Google ScholarGoogle Scholar
  59. I. Singh, D. Kumar, and S. K. Khatri. 2019. Improving the efficiency of e-healthcare system based on cloud. In Proceedings of the Amity International Conference on Artificial Intelligence. 930–933. DOI: 10.1109/AICAI.2019.8701387Google ScholarGoogle Scholar
  60. R. Thanki and K. Borisagar. 2015. Biometric watermarking technique based on CS theory and fast discrete curvelet transform for face and fingerprint protection. Adv. Sig. Proc. Intell. Recog. Syst. 425 (2015), 133–144. DOI: 10.1007/978-3-319-28658-7Google ScholarGoogle Scholar
  61. C. Zhang, L. L. Cheng, S. Member, Z. Qiu, and L. M. Cheng. 2008. Multipurpose watermarking based on multiscale curvelet transform. IEEE Trans. Inf. Forens. Secur. 3, 4 (2008), 611–619. Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. J. Xu, H. Pang, and J. Zhao. 2010. Digital image watermarking algorithm based on fast curvelet transform. J. Softw. Eng. Appl. 03, 10 (2010), 939–943. DOI: 10.4236/jsea.2010.310111Google ScholarGoogle ScholarCross RefCross Ref
  63. B. Shanthini and S. Swamynathan. 2012. Genetic-based biometric security system for wireless sensor-based health care systems. In Proceedings of the International Conference on Recent AdvAnces in Computer Software Systems. 180–184. DOI: 10.1109/RACSS.2012.6212720Google ScholarGoogle Scholar
  64. R. Ali and A. K. Pal. 2018. Cryptanalysis and biometric-based enhancement of a remote user authentication scheme for e-healthcare system. Arab. J. Sci. Eng. 43, 12 (2018), 7837–7852. DOI: 10.1007/s13369-018-3220-4Google ScholarGoogle ScholarCross RefCross Ref
  65. S. H. Islam. 2016. Design and analysis of an improved smartcard-based remote user password authentication scheme. Int. J. Commun. Syst. 29 (2016), 1708–1719. DOI: 10.1002/dac.2793 Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. Jin Wook Byun. 2015. Privacy preserving smartcard-based authentication system with provable security. Secur. Commun. Netw. 8, 17 (2015), 3028–3044, DOI: 10.1002/sec Google ScholarGoogle ScholarCross RefCross Ref
  67. A. K. Awasthi, K. Srivastava, and R. C. Mittal. 2011. An improved timestamp-based remote user authentication scheme. Comput. Electr. Eng 37, 6 (2011), 869–874, DOI: 10.1016/j.compeleceng.2011.09.015 Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. R. Mishra and A. K. Barnwal. 2015. A privacy preserving secure and efficient authentication scheme for telecare medical information systems. J. Med. Syst. 39, 5 (2015), 1–10. DOI: 10.1007/s10916-015-0215-5 Google ScholarGoogle ScholarDigital LibraryDigital Library
  69. D. Giri, T. Maitra, R. Amin, and P. D. Srivastava. 2015. An efficient and robust RSA-based remote user authentication for telecare medical information systems. J. Med. Syst. 39, 1 (2015). DOI: 10.1007/s10916-014-0145-7 Google ScholarGoogle ScholarDigital LibraryDigital Library
  70. S. Kumari, M. K. Gupta, M. K. Khan, and X. Li. 2013. An improved timestamp-based password authentication scheme: comments, cryptanalysis, and improvement, secure communication network. Secur. Commun. Netw. 7, 11 (2013), 1921–1932. DOI: 10.1002/sec.906 Google ScholarGoogle ScholarDigital LibraryDigital Library
  71. H. Hamidi. 2019. An approach to develop the smart health using internet of things and authentication based on biometric technology. Fut. Gen. Comput. Syst. 91 (2019), 434–449. DOI: 10.1016/j.future.2018.09.024Google ScholarGoogle ScholarDigital LibraryDigital Library
  72. J. J. Hathaliya, S. Tanwar, S. Tyagi, and N. Kumar. 2019. Securing electronics healthcare records in healthcare 4.0: A biometric-based approach. Comput. Electr. Eng 76 (2019), 398–410. DOI: 10.1016/j.compeleceng.2019.04.017Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. X. Li, M. H. Ibrahim, S. Kumari, A. K. Sangaiah, V. Gupta, and K. K. R. Choo. 2017. Anonymous mutual authentication and key agreement scheme for wearable sensors in wireless body area networks. Comput. Netw. 129 (2017), 429–443. DOI: 10.1016/j.comnet.2017.03.013 Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. Z. Zhao. 2014. An efficient anonymous authentication scheme for wireless body area networks using elliptic curve cryptosystem. J. Med. Syst. 38, 2 (2014). DOI: 10.1007/s10916-014-0013-5 Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. S. Mirjalol and T. K. Whangbo. 2018. An authentication protocol for smartphone integrated ambient assisted living system. In Proceedings of the 9th International Information Communication Technologies Conference. 424–428. DOI: 10.1109/ICTC.2018.8539365Google ScholarGoogle Scholar
  76. X. Li, J. Niu, M. Z. A. Bhuiyan, F. Wu, M. Karuppiah, and S. Kumari. 2018. A robust ECC-based provable secure authentication protocol with privacy preserving for industrial internet of things. IEEE Trans. Industr. Inform. 14, 8 (2018), 3599–3609. DOI: 10.1109/TII.2017.2773666Google ScholarGoogle ScholarCross RefCross Ref
  77. Y. Choi, D. Lee, J. Kim, J. Jung, J. Nam, and D. Won. 2014. Security enhanced user authentication protocol for wireless sensor networks using elliptic curves cryptography. Sensors (Switzerland), 14, 6 (2014), 10081–10106. DOI: 10.3390/s140610081Google ScholarGoogle ScholarCross RefCross Ref
  78. X. Li, J. Niu, S. Kumari, F. Wu, A. K. Sangaiah, and K. K. R. Choo. 2018. A three-factor anonymous authentication scheme for wireless sensor networks in internet of things environments. J. Netw. Comput. Appl. 103, 1 (2018), 194–204. DOI: 10.1016/j.jnca.2017.07.001 Google ScholarGoogle ScholarDigital LibraryDigital Library
  79. P. Chhajed, D. Baviskar, R. Ahire, A. Bumb, and M. V. Korade. 2016. Certificateless remote anonymous authentication technique for wireless body area networks. In Proceedings of the International Conference on Green Computing and Internet of Things 25, 2 (2016), 1035–1041. DOI: 10.1109/ICGCIoT.2015.7380616 Google ScholarGoogle ScholarDigital LibraryDigital Library
  80. Q. Jiang, J. Ma, F. Wei, Y. Tian, J. Shen, and Y. Yang. 2016. An untraceable temporal-credential-based two-factor authentication scheme using ECC for wireless sensor networks. J. Netw. Comput. Appl. 76 (2015), 37–48. DOI: 10.1016/j.jnca.2016.10.001 Google ScholarGoogle ScholarDigital LibraryDigital Library
  81. J. Srinivas, A. K. Das, M. Wazid, and N. Kumar. 2018. Anonymous lightweight chaotic map-based authenticated key agreement protocol for industrial internet of things. IEEE Trans. Depend. Secur. Comput. 5971 (2018). DOI: 10.1109/TDSC.2018.2857811Google ScholarGoogle Scholar
  82. P. Singh, B. Raman, and P. P. Roy. 2017. A multimodal biometric watermarking system for digital images in redundant discrete wavelet transform. Multimed. Tools Appl. 76, 3 (2017), 3871–3897. DOI: 10.1007/s11042-016-4048-0 Google ScholarGoogle ScholarDigital LibraryDigital Library
  83. V. Matyas and Z. Riha. 2010. Security of biometric authentication systems. Proceedings of the International Conference on Computer Information Systems and Industrial Management Applications. 19–28. DOI: 10.1109/CISIM.2010.5643698Google ScholarGoogle Scholar
  84. A. K. Singh. 2020. Data hiding: Current trends, innovation and potential challenges. ACM Trans. Multimed. Comput. Commun. Appl. (2020). DOI: 10.1145/3382772 Google ScholarGoogle ScholarDigital LibraryDigital Library
  85. N. Agarwal, A. K. Singh, and P. K. Singh. 2019. Survey of robust and imperceptible watermarking. Multimed. Tools Appl. 78, 7 (2019), 8603–8633. DOI: 10.1007/s11042-018-7128-5 Google ScholarGoogle ScholarDigital LibraryDigital Library
  86. R. Acharya U. S. Subbanna Bhat, S. Kumar, and L. C. Min. 2003. Transmission and storage of medical images with patient information. Comput. Biol. Med. 33, 4 (2003), 303–310. DOI: 10.1016/S0010-4825(02)00083-5Google ScholarGoogle ScholarCross RefCross Ref
  87. K. S. Sankaran, H. Abhi Rayna, V. Mangu, V. R. Prakash, and N. Vasudevan. 2019. Image water marking using DWT to encapsulate data in medical image. In Proceedings of the IEEE International Conference on Communications and Signal Processing. 568–571. DOI: 10.1109/ICCSP.2019.8698057Google ScholarGoogle Scholar
  88. K. J. Kavitha and P. B. Shan. 2019. An efficient medical image watermarking technique using integer wavelet transform and quick/fast response codes. Int. J. Intell. Syst. Technol. Appl. 18, 3 (2019), 271–280. DOI: 10.1504/IJISTA.2019.099344Google ScholarGoogle ScholarDigital LibraryDigital Library
  89. S. Thakur, A. K. Singh, S. P. Ghrera, and M. Elhoseny. 2019. Multi-layer security of medical data through watermarking and chaotic encryption for tele-health applications. Multimed. Tools Appl. 78, 3 (2019), 3457–3470. DOI: 10.1007/s11042-018-6263-3 Google ScholarGoogle ScholarDigital LibraryDigital Library
  90. A. K. Singh, M. Dave, and A. Mohan. 2014. Hybrid technique for robust and imperceptible image watermarking in DWT-DCT-SVD domain. Nat. Acad. Sci. Lett. 37, 4 (2014), 351–358. DOI: 10.1007/s40009-014-0241-8Google ScholarGoogle ScholarCross RefCross Ref
  91. M. I. Khan, M. M. Rahman, and M. I. H. Sarker. 2013. Digital watermarking for image authentication based on combined DCT, DWT and SVD transformation. Int. J. Comput. Sci. 10, 3 (2013).Google ScholarGoogle Scholar
  92. R. Mothi and M. Karthikeyan. 2019. Protection of bio medical iris image using watermarking and cryptography with WPT. Measurement 136 (2019), 67–73. DOI: 10.1016/j.measurement.2018.12.030Google ScholarGoogle ScholarCross RefCross Ref
  93. M. F. Mohammed El Bireki, M. F. L. Abdullah, A. A. M. Ukasha, and A. A. Elrowayati. 2016. Digital image watermarking based on joint (DCT-DWT) and Arnold transform. Int. J. Secur. Appl. 10, 5 (2016), 107–118. DOI: 10.14257/ijsia.2016.10.5.10Google ScholarGoogle Scholar
  94. F. N. Thakkar and V. K. Srivastava. 2017. A blind medical image watermarking: DWT-SVD based robust and secure approach for telemedicine applications. Multimed. Tools Appl. 76, 3 (2017), 3669–3697. DOI: 10.1007/s11042-016-3928-7 Google ScholarGoogle ScholarDigital LibraryDigital Library
  95. S. A. Parah, J. A. Sheikh, F. Ahad, N. A. Loan, and G. M. Bhat. 2017. Information hiding in medical images: A robust medical image watermarking system for E-healthcare. Multimed. Tools Appl. 76, 8 (2017), 10599–10633. DOI: 10.1007/s11042-015-3127-y Google ScholarGoogle ScholarDigital LibraryDigital Library
  96. R. Eswaraiah and E. S. Reddy. 2014. A fragile ROI-based medical image watermarking technique with tamper detection and recovery. In Proceedings of the 4th International Conference on Communication Systems Network Technology. 896–899. DOI: 10.1109/CSNT.2014.184 Google ScholarGoogle ScholarDigital LibraryDigital Library
  97. R. Pandey, A. K. Singh, B. Kumar, and A. Mohan. 2016. Iris based secure NROI multiple eye image watermarking for teleophthalmology. Multimed. Tools Appl. 75, 22 (2016), 14381–14397. DOI: 10.1007/s11042-016-3536-6 Google ScholarGoogle ScholarDigital LibraryDigital Library
  98. A. K. Singh, M. Dave, and A. Mohan. 2015. Robust and secure multiple watermarking in wavelet domain. J. Med. Imaging Heal. Informatics 5, 2 (2015), 406–414. DOI: 10.1166/jmihi.2015.1407Google ScholarGoogle ScholarCross RefCross Ref
  99. A. Al-Haj and A. Amer. 2014. Secured telemedicine using region-based watermarking with tamper localization. J. Digit. Imaging 27, 6 (2014), 737–750. DOI: 10.1007/s10278-014-9709-9Google ScholarGoogle ScholarCross RefCross Ref
  100. A. K. Singh, B. Kumar, M. Dave, and A. Mohan. 2015. Multiple watermarking on medical images using selective discrete wavelet transform coefficients. J. Med. Imaging Heal. Informatics 5, 3 (2015), 607–614. DOI: 10.1166/jmihi.2015.1432Google ScholarGoogle ScholarCross RefCross Ref
  101. B. Kumar, H. V. Singh, S. P. Singh, and A. Mohan. 2011. Secure spread-spectrum watermarking for telemedicine applications. J. Inf. Secur. 02, 02 (2011), 91–98. DOI: 10.4236/jis.2011.22009Google ScholarGoogle Scholar
  102. B. Kumar, A. Anand, S. P. Singh, and A. Mohan. 2011. High capacity spread-spectrum watermarking for telemedicine applications. World Acad. Sci. Eng. Technol. 79, 7 (2011), 95–99. DOI: 10.5281/zenodo.1059548Google ScholarGoogle Scholar
  103. S. Boucherkha and M. Benmohamed. 2007. A lossless watermarking based authentication system for medical images. World Acad. Sci. Eng. Technol. Int. J. Medical, Heal. Biomed. Bioeng. Pharm. Eng 1, 1 (2007), 20–23.Google ScholarGoogle Scholar
  104. F. Casino, T. K. Dasaklis, and C. Patsakis. 2018. A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telemat. Informatics 36 (2018), 55–81. DOI: 10.1016/j.tele.2018.11.006Google ScholarGoogle ScholarCross RefCross Ref
  105. X. Li, P. Jiang, T. Chen, X. Luo, and Q. Wen. 2020. A survey on the security of blockchain systems. Fut. Gen. Comput. Syst. 107 (2020), 841–853. DOI: 10.1016/j.future.2017.08.020Google ScholarGoogle ScholarDigital LibraryDigital Library
  106. C. Agbo, Q. Mahmoud, and J. Eklund. 2019. Blockchain technology in healthcare: A systematic review. Healthcare 7, 2 (2019), 56. DOI: 10.3390/healthcare7020056Google ScholarGoogle ScholarCross RefCross Ref
  107. I. C. Lin and T. C. Liao. 2017. A survey of blockchain security issues and challenges. Int. J. Netw. Secur 19, 5 (2017), 653–659. DOI: 10.6633/IJNS.201709.19(5).01Google ScholarGoogle Scholar
  108. H. Kaur, M. A. Alam, R. Jameel, A. K. Mourya, and V. Chang. 2018. A proposed solution and future direction for blockchain-based heterogeneous medicare data in cloud environment. J. Med. Syst. 42, 8 (2018). DOI: 10.1007/s10916-018-1007-5 Google ScholarGoogle ScholarDigital LibraryDigital Library
  109. Y. Chen, S. Ding, Z. Xu, H. Zheng, and S. Yang. 2018. Blockchain-based medical records secure storage and medical service framework. J. Med. Syst. 43, 1 (2018). DOI: 10.1007/s10916-018-1121-4 Google ScholarGoogle ScholarDigital LibraryDigital Library
  110. S. Wu and J. Du. 2019. Electronic medical record security sharing model based on blockchain. Proceedings of the ACM International Conference on Cryptography, Security and Privacy. 13–17. DOI: 10.1145/3309074.3309079 Google ScholarGoogle ScholarDigital LibraryDigital Library
  111. L. Zhu, H. Dong, M. Shen, and K. Gai. 2019. An incentive mechanism using Shapley value for blockchain-based medical data sharing. In Proceedings of the 5th IEEE International Conference on Big Data Security on Cloud, 5th IEEE International Conference on High Performance Smart Computing, and 4th IEEE International Conference on Intelligent Data Security. 113–118. DOI: 10.1109/BigDataSecurity-HPSC-IDS.2019.00030Google ScholarGoogle Scholar
  112. M. Shen, Y. Deng, L. Zhu, X. Du, and N. Guizani. 2019. Privacy-preserving image retrieval for medical IoT systems: A blockchain-based approach. IEEE Netw. 33, 5 (2019), 27–33. DOI: 10.1109/MNET.001.1800503Google ScholarGoogle ScholarDigital LibraryDigital Library
  113. L. Brunese, F. Mercaldo, A. Reginelli, and A. Santone. 2019. A blockchain based proposal for protecting healthcare systems through formal methods. Procedia Comput. Sci. 159 (2019), 1787–1794. DOI: 10.1016/j.procs.2019.09.350Google ScholarGoogle ScholarDigital LibraryDigital Library
  114. A. Theodouli, S. Arakliotis, K. Moschou, K. Votis, and D. Tzovaras. 2018. On the design of a blockchain-based system to facilitate healthcare data sharing. In Proceedings of the 17th IEEE International Conference on Trust, Security and Private Computer Communications, and 12th IEEE International Conference on Big Data Sciience Engineering and Trust. 1374–1379. DOI: 10.1109/TrustCom/BigDataSE.2018.00190Google ScholarGoogle Scholar
  115. K. Fan, S. Wang, Y. Ren, H. Li, and Y. Yang. 2018. Systems-level quality improvement MedBlock: Efficient and secure medical data sharing via blockchain. J. Med. Syst. 42, (2018) 1–11. DOI: 10.1007/s10916-018-0993-7Google ScholarGoogle ScholarDigital LibraryDigital Library
  116. D. Ichikawa, M. Kashiyama, and T. Ueno. 2017. Tamper-resistant mobile health using blockchain technology. JMIR mHealth uHealth. 5, 7 (2017), 1–10. DOI: 10.2196/mhealth.7938Google ScholarGoogle Scholar
  117. F. Xhafa, J. Li, G. Zhao, J. Li, X. Chen, and D. S. Wong. 2015. Designing cloud-based electronic health record system with attribute-based encryption. Multimed. Tools Appl 74, 10 (2015), 3441–3458. DOI: 10.1007/s11042-013-1829-6 Google ScholarGoogle ScholarDigital LibraryDigital Library
  118. S. Alshehri, S. P. Radziszowski, and R. K. Raj. 2012. Secure access for healthcare data in the cloud using ciphertext-policy attribute-based encryption. In Proceedings of the IEEE 28th International Conference on Data Engineering Work. 143–146. DOI: 10.1109/ICDEW.2012.68 Google ScholarGoogle ScholarDigital LibraryDigital Library
  119. K. Yang, X. Jia, K. Ren, and B. Zhang. 2013. DAC-MACS: Effective data access control for multi-authority cloud storage systems. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’13). 2895–2903. DOI: 10.1109/INFCOM.2013.6567100Google ScholarGoogle Scholar
  120. N. Garg, M. Wazid, A. K. Das, D. P. Singh, J. J. P. C. Rodrigues, and Y. Park. 2020. BAKMP-IoMT: Design of blockchain enabled authenticated key management protocol for internet of medical things deployment. IEEE Access 8 (2020), 95956–95977. DOI: 10.1109/ACCESS.2020.2995917Google ScholarGoogle ScholarCross RefCross Ref
  121. C. S. Jang, D. G. Lee, J. Han, and J. H. Park. 2011. Hybrid security protocol for wireless body area networks. Wirel. Commun. Mob. Comput. 11, 2 (2011), 277–288. DOI: 10.1002/wcm Google ScholarGoogle ScholarCross RefCross Ref
  122. D. He and S. Zeadally. 2015. Authentication protocol for an ambient assisted living system. IEEE Commun. Mag. 53, 1 (2015), 71–77. DOI: 10.1109/MCOM.2015.7010518Google ScholarGoogle ScholarDigital LibraryDigital Library
  123. F. Merabet, A. Cherif, M. Belkadi, O. Blazy, E. Conchon, and D. Sauveron. 2020. New efficient M2C and M2M mutual authentication protocols for IoT-based healthcare applications. Peer-to-Peer Netw. Appl. 13, 2 (2020), 439–474. DOI: 10.1007/s12083-019-00782-8Google ScholarGoogle ScholarCross RefCross Ref

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