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              <text>Cyber-Secure Framework for the Insecure Designs in Healthcare Industry</text>
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              <text>blockchain; cleartext storage; Cyber Security; insecure design; machine learning; sensitive data</text>
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              <text>Sensitive data protection has been a top priority in the healthcare industry. This has led to the investigation of safe data storage and transaction. Despite various attempts to address this issue, data breaches continue to plague the healthcare industry. This study aims to investigate prevalent storage practices and security methodologies in the healthcare, recognizing the need for a robust framework. The work further extends with design of new security framework for healthcare industry. This framework identifies critical data and implement measures to prevent unauthorized access and data tempering. The industrial hype towards the implementation of adaptive machine learning craves the need for hybrid machine learning approaches to be adapted in the cyber secure framework. In order to improve security and confidentiality in the healthcare sector. Blockchain is used in the proposed cyber secure framework promising integrity of data with the features of immutability. This proposal aims to provide a comprehensive solution to the ongoing problem of protecting medical data.  Grenze Scientific Society, 2024.</text>
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              <text>Mansoor N.; Sandeep J.</text>
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              <text>15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024, Vol-2, pp. 3824-3832.</text>
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              <text>Grenze Scientific Society</text>
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              <text>ISBN: 979-833130057-9</text>
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              <text>Mansoor N., Department of computer science, CHRIST (Deemed to be University), Bangalore, India; Sandeep J., Department of computer science, CHRIST (Deemed to be University), Bangalore, India</text>
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