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Artificial Intelligence-Based Ethical Hacking for Health Information Systems: Simulation Study.

Ying He1, Efpraxia Zamani2, Iryna Yevseyeva3

  • 1School of Computer Science, University of Nottingham, Nottingham, United Kingdom.

Journal of Medical Internet Research
|April 25, 2023
PubMed
Summary
This summary is machine-generated.

An optimized, AI-based ethical hacking method significantly improves health information system (HIS) cybersecurity by identifying vulnerabilities more efficiently than traditional methods. This advanced approach enhances the protection of sensitive health data against cyber threats.

Keywords:
AI-based hackingHISOpenEMRartificial intelligencecyber defense solutionsethical hackinghealth information systemopen-source electronic medical record

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Area of Science:

  • Cybersecurity
  • Health Informatics
  • Artificial Intelligence

Background:

  • Health information systems (HISs) face persistent cyber threats, risking critical health infrastructure and sensitive patient data.
  • Current cybersecurity research in healthcare disproportionately focuses on medical devices and data, neglecting systematic investigation of HIS vulnerabilities.
  • There's a recognized gap in understanding how attackers breach HISs to access electronic health records.

Purpose of the Study:

  • To introduce a novel, AI-based optimized ethical hacking methodology for HIS cybersecurity.
  • To systematically compare the efficacy of this optimized method against traditional unoptimized ethical hacking.
  • To enhance the identification of penetration attack vectors and pathways within HIS environments.

Main Methods:

  • Developed and implemented an optimized, AI-driven ethical hacking approach for HIS.
  • Utilized an experimental setting with an OpenEMR system simulation adhering to NIST's ethical hacking framework.
  • Conducted 50 attack rounds comparing the optimized method with a traditional unoptimized ethical hacking technique.

Main Results:

  • The optimized ethical hacking method demonstrated superior performance over the unoptimized approach.
  • Key performance metrics showing improvement include reduced average attack time and increased average exploit success rates.
  • Identified specific successful attack paths and exploits, including remote code execution and authentication vulnerabilities.

Conclusions:

  • Systematic ethical hacking, particularly with AI optimization, offers significant improvements for HIS cybersecurity.
  • The findings provide valuable insights for protecting widely adopted systems like OpenEMR and advancing HIS cybersecurity research.
  • This research addresses weaknesses in current HIS cybersecurity and ethical hacking methodologies, offering practical benefits to the healthcare sector.