Emerging Trends in Medical Science Using Biometric

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Emerging Technologies in Data Mining and Information Security

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1286))

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Abstract

Biometrics in health care and medicine is one of the revolutionary technological advancement that has been made to improve and cater the requirements of patients as well as doctors. Technologies have continued to progress, affecting the performance of globally efficient medical healthcare systems. Meanwhile, privacy and security of patient data for most users of the health information management system have recorded major concerns. This is not denying the fact that privacy is necessary in-patient care. The record of the patient which may be inadequately retained or misconstrued may lead to wrong prescriptions or death. In this paper, we present an overview and application of biometric in medical science is discussed in detail. The use of biometrics for identification has played a major role in protecting privacy and medical healthcare systems. This paper also justifies the classical methods, influential methods, and taxonomy predicated on the biometric attributes.

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References

  1. Prasad, P.S.: Vulnerabilities of biometric authentication systems: a survey. Helix 8(5), 4100–4103 (2018). https://doi.org/10.29042/2018-4100-4103

    Article  Google Scholar 

  2. Roy, S., Chatterjee, S., Das, A.K., Chattopadhyay, S., Kumari, S., Jo, M.: Chaotic map-based anonymous user authentication scheme with user biometrics and fuzzy extractor for crowdsourcing internet of things. IEEE Internet Things J. 5(4), 2884–2895 (2018). https://doi.org/10.1109/jiot.2017.2714179

    Article  Google Scholar 

  3. Ali, R., Pal, A.K.: An efficient three factor-based authentication scheme in multiserver environment using ECC. Int. J. Commun. Syst. 31(4) (2017). https://doi.org/10.1002/dac.3484

  4. Barman, S., Shum, H.P.H., Chattopadhyay, S., Samanta, D.: A secure authentication protocol for multi-server-based E-healthcare using a fuzzy commitment scheme. IEEE Access 7, 12557–12574 (2019). https://doi.org/10.1109/access.2019.2893185

    Article  Google Scholar 

  5. Goyal, S., Sharma, N., Bhushan, B., Shankar, A., Sagayam, M.: IoT enabled technology in secured healthcare: applications, challenges and future directions. In: Hassanien, A.E., Khamparia, A., Gupta, D., Shankar, K., Slowik, A. (eds.) Cognitive Internet of Medical Things for Smart Healthcare. Studies in Systems, Decision and Control, vol. 311. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-55833-8_2

  6. Mehmood, Z., Ghani, A., Chen, G., Alghamdi, A.S.: Authentication and secure key management in E-health services: a robust and efficient protocol using biometrics. IEEE Access 7, 113385–113397 (2019). https://doi.org/10.1109/access.2019.2935313

    Article  Google Scholar 

  7. Song, Y.-J.: Data Access Control Scheme in Health Cloud Environment (2016). https://doi.org/10.14257/astl.2016.133.24

  8. Khamparia, A., Gupta, D., de Albuquerque, V.H.C., Sangaiah, A.K., Jhaveri, R.H.: Internet of health things driven deep learning system for detection and classification of cervical cells using transfer learning. J. Supercomput. (2020). https://doi.org/10.1007/s11227-020-03159-4

  9. Mao, D., Liu, H., Zhang, W.: An enhanced three-factor authentication scheme with dynamic verification for medical multimedia information systems. IEEE Access 7, 167683–167695 (2019). https://doi.org/10.1109/access.2019.2953532

    Article  Google Scholar 

  10. Tomlinson, W.J., Banou, S., Blechinger-Slocum, S., Yu, C., Chowdhury, K.R.: Body-guided galvanic coupling communication for secure biometric data. IEEE Trans. Wirel. Commun. 18(8), 4143–4156 (2019). https://doi.org/10.1109/twc.2019.2921964

    Article  Google Scholar 

  11. Gaur, J., Goel, A.K., Rose, A., Bhushan, B.: Emerging trends in machine learning. In: 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT) (2019). https://doi.org/10.1109/icicict46008.2019.8993192

  12. Li, X., Peng, J., Obaidat, M.S., Wu, F., Khan, M.K., Chen, C.: A secure three-factor user authentication protocol with forward secrecy for wireless medical sensor network systems. IEEE Syst. J. 14(1), 39–50 (2020). https://doi.org/10.1109/jsyst.2019.2899580

    Article  Google Scholar 

  13. Khatoon, S., Rahman, S.M.M., Alrubaian, M., Alamri, A.: Privacy-preserved, provable secure, mutually authenticated key agreement protocol for healthcare in a smart city environment. IEEE Access 7, 47962–47971 (2019). https://doi.org/10.1109/access.2019.2909556

    Article  Google Scholar 

  14. Yang, W., Wang, S., Hu, J., Zheng, G., Chaudhry, J., Adi, E., Valli, C.: Securing mobile healthcare data: a smart card based cancelable finger-vein bio-cryptosystem. IEEE Access 6, 36939–36947 (2018). https://doi.org/10.1109/access.2018.2844182

    Article  Google Scholar 

  15. Dong, M., Ansari, N.: Guest editorial: special section on cyber-physical social systems—integrating human into computing. IEEE Trans. Emerg. Top. Comput. 8(1), 4–5 (2020). https://doi.org/10.1109/tetc.2019.2934339

    Article  Google Scholar 

  16. Sharma, A., Sharma, N., Kaushik, I., Kumar, S., Khatoon, N.: Predictive analysis of type 2 diabetes using hybrid ML model and IoT. In IoT Security Paradigms and Applications, pp. 303-320. CRC Press (2020)

    Google Scholar 

  17. Sadhya, D., Singh, S.K.: Construction of a Bayesian decision theory-based secure multimodal fusion framework for soft biometric traits. IET Biom. 7(3), 251–259 (2018). https://doi.org/10.1049/iet-bmt.2017.0049

    Article  Google Scholar 

  18. Nguyen, T.A.T., Dang, T.K.: Privacy preserving biometric-based remote authentication with secure processing unit on untrusted server. IET Biom. 8(1), 79–91 (2019). https://doi.org/10.1049/iet-bmt.2018.5101

    Article  MathSciNet  Google Scholar 

  19. Harjani, M., Grover, M., Sharma, N., Kaushik, I.: Analysis of various machine learning algorithm for cardiac pulse prediction. In: 2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) (2019). https://doi.org/10.1109/icccis48478.2019.8974519

  20. Comparative analysis of 3-D password using various techniques. Int. J. Emerg. Technol. Innov. Res. 6(6), 711–718 (2019). (www.jetir.org). ISSN: 2349-5162. https://www.jetir.org/papers/JETIR1907Q08.pdf

  21. Sharma, N., Kaushik, I., Bhushan, B., Gautam, S., Khamparia, A.: Applicability of WSN and biometric models in the field of healthcare. In: Deep learning strategies for Security Enhancement in Wireless Sensor Networks Advances in Information Security, Privacy, and Ethics, pp. 304–329 (2020). https://doi.org/10.4018/978-1-7998-5068-7.ch016

  22. Sathyadevan, S., Achuthan, K., Doss, R., Pan, L.: Protean authentication scheme—a time-bound dynamic KeyGen authentication technique for IoT edge nodes in outdoor deployments. IEEE Access 7, 92419–92435 (2019). https://doi.org/10.1109/access.2019.2927818

    Article  Google Scholar 

  23. Singh, A., Mehta, J.C., Anand, D., Nath, P., Pandey, B., Khamparia, A.: An intelligent hybrid approach for hepatitis disease diagnosis: combining enhanced k-means clustering and improved ensemble learning. Expert Syst. (Wiley) (2020). https://doi.org/10.1111/exsy.12526

  24. Kim, S.-K., Yeun, C.Y., Yoo, P.D.: An enhanced machine learning-based biometric authentication system using RR-interval framed electrocardiograms. IEEE Access 7, 168669–168674 (2019). https://doi.org/10.1109/access.2019.2954576

    Article  Google Scholar 

  25. Komeili, M., Louis, W., Armanfard, N., Hatzinakos, D.: Feature selection for nonstationary data: application to human recognition using medical biometrics. IEEE Trans. Cybern. 48(5), 1446–1459 (2018). https://doi.org/10.1109/tcyb.2017.2702059

    Article  Google Scholar 

  26. Hammad, M., Liu, Y., Wang, K.: Multimodal biometric authentication systems using convolution neural network based on different level fusion of ECG and fingerprint. IEEE Access 7, 26527–26542 (2019). https://doi.org/10.1109/access.2018.2886573

    Article  Google Scholar 

  27. Kaur, R., Kaur, K., Khamparia, A., Anand, D.: An improved and adaptive approach in ANFIS to predict knee diseases. Int. J. Healthcare Inf. Syst. Inf. (IJHISI). IGI Global 15(2), 22–37 (2020)

    Google Scholar 

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Correspondence to Nitin Tyagi .

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Tyagi, N., Bhushan, B., Vijay, S., Yadav, H., Gautam, S. (2021). Emerging Trends in Medical Science Using Biometric. In: Hassanien, A.E., Bhattacharyya, S., Chakrabati, S., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 1286. Springer, Singapore. https://doi.org/10.1007/978-981-15-9927-9_56

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