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Intelligent, Secure Big Health Data Management Using Deep Learning and Blockchain Technology: An Overview

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Book cover Deep Learning Techniques for Biomedical and Health Informatics

Part of the book series: Studies in Big Data ((SBD,volume 68))

Abstract

Sensor-based health data collection, remote access to health data to render real-time advice have been the key advantages of smart and remote healthcare. Such health monitoring and support are getting immensely popular among both patients and doctors as it does not require physical movement which is always not possible for elderly people who lives mostly alone in current socio-economic situations. Healthcare Informatics plays a key role in such circumstances. The huge amount of raw data emanating from sensors needs to be processed applying machine learning and deep learning algorithms for useful information extraction to develop an intelligent knowledge base for providing an appropriate solution as and when required. The real challenge lies in data storage and retrieval preserving security, privacy, reliability and availability requirements. Health data saved in Electronic medical record (EMR) is generally saved in a client-server database where central coordinator does access control like create, access, update, or delete of health records. But in smart and remote healthcare supported by enabling technologies such as Sensors, Internet of Things (IoT), Cloud, Deep learning, Big data, etc. EMR needs to be accessed in a distributed manner among multiple stakeholders involved such as hospitals, doctors, research labs, patients’ relatives, insurance provider, etc. Hence, it is to be ensured that health data be protected from unauthorized access specifically to maintain data integrity using advanced distributed security techniques such as blockchain.

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Acknowledgements

This work has been carried out as a part of sanctioned research project from Government of West Bengal, Department of Science & Technology and Biotechnology, project sanction no. 230(Sanc)/ST/P/S&T/6G-14/2018.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

    Sohail Saif & Suparna Biswas

  2. Department of Information Technology, Jadavpur University, Kolkata, West Bengal, India

    Samiran Chattopadhyay

Authors
  1. Sohail Saif
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  2. Suparna Biswas
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  3. Samiran Chattopadhyay
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Corresponding author

Correspondence to Suparna Biswas .

Editor information

Editors and Affiliations

  1. Department of Computer Science, North Orissa University, Takatpur, Odisha, India

    Sujata Dash

  2. School of Computer Science and Engineering, KIIT Deemed to University, Bhubaneswar, Odisha, India

    Biswa Ranjan Acharya

  3. Computer Science and Engineering Department, G. B. Pant Government Engineering College, New Delhi, Delhi, India

    Mamta Mittal

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, AL, USA

    Ajith Abraham

  5. Department of Organizational Systems and Adult Health, University of Maryland, Baltimore, MD, USA

    Arpad Kelemen

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Saif, S., Biswas, S., Chattopadhyay, S. (2020). Intelligent, Secure Big Health Data Management Using Deep Learning and Blockchain Technology: An Overview. In: Dash, S., Acharya, B., Mittal, M., Abraham, A., Kelemen, A. (eds) Deep Learning Techniques for Biomedical and Health Informatics. Studies in Big Data, vol 68. Springer, Cham. https://doi.org/10.1007/978-3-030-33966-1_10

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