Database security in psychiatry: leveraging large language models and blockchain for secure data management

Authors

  • Joel Nithish Kumar Murugan * Illinois Institute of Technology, Chicago, Illinois, United States of America
  • Padmavathi Vyshnavi Madarampalli Illinois Institute of Technology, Chicago, Illinois, United States of America
  • Shashikant Ramesh Yadav Illinois Institute of Technology, Chicago, Illinois, United States of America

https://doi.org/10.22105/metaverse.v1i2.63

Abstract

In the current digital age, effectively managing psychiatric data has emerged as a significant challenge due to the highly sensitive nature of the information involved—from personal histories to therapy notes, behaviors, and diagnostic results. Unauthorized access or mishandling of this data could result in privacy violations, discrimination, and a further decline in trust in mental health systems. This paper examines how two disruptive technologies—Large Language Models (LLMs) and Blockchain—collaborate to overcome these challenges. LLMs are particularly adept at processing unstructured data, offering in-depth and insightful clinical analytics for tailored mental health interventions while ensuring patient confidentiality is upheld. Blockchain technology guarantees data integrity, immutability, and decentralized storage, enhancing security and enabling controlled access to sensitive psychiatric records. The merger of these technologies will create a secure, efficient, and privacy-respecting system for managing psychiatric data, which will enhance clinical decision-making and safeguard patient trust. The suggested framework will incorporate a Blockchain-based decentralized storage component, a data analytics layer supported by LLMs, and a secure interface for regulated access to data that adheres to ethical and regulatory standards. This integration represents a significant advancement in addressing the unique challenges associated with managing psychiatric data in healthcare.

Keywords:

Large language models, Secure data storage, Privacy-preserving, Blockchain

References

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Published

2024-03-23

Issue

Vol. 1 No. 2 (2024): Metaversalize

Section

Articles

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How to Cite

Murugan, J. N. K. ., Madarampalli, P. V. ., & Yadav, S. R. . (2024). Database security in psychiatry: leveraging large language models and blockchain for secure data management. Metaversalize, 1(2), 81-90. https://doi.org/10.22105/metaverse.v1i2.63
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