paperJune 2026Unreviewed

Information Security and Clinical Ethics in LLM-Based Healthcare Systems

Updesh Kumar Jaiswal, Jaishree Jain, Harnit Saini, Amrita Bhatnagar, Pushpendra Singh, Shashank Sahu, Khushbu Malviya

Abstract

Large Language Models (LLMs) play a complex and ever-evolving role in medicine. LLMs, in general, can help medical professionals identify patients by giving them fast, data-driven information. They are able to analyse patient data, compare it with a comprehensive medical history, and make recommendations for potential diagnoses or identify issues that need more research. This chapter examines the threats that prompt injection attacks, perfect overturn, and data leak could pose to PHI and

Framework mappings

OWASP Top 10 for LLM Applications

LLM01Prompt Injection

MITRE ATLAS

AML.T0051LLM Prompt Injection

Suggested from the entry's categories.

Cite

@misc{jaiswal2026information,
  title = {{Information Security and Clinical Ethics in LLM-Based Healthcare Systems}},
  author = {Updesh Kumar Jaiswal and Jaishree Jain and Harnit Saini and Amrita Bhatnagar and Pushpendra Singh and Shashank Sahu and Khushbu Malviya},
  year = {2026},
  month = jun,
  doi = {10.4018/979-8-3373-7862-6.ch004},
  url = {https://doi.org/10.4018/979-8-3373-7862-6.ch004}
}