The Challenges of Data Privacy and Cybersecurity in Cloud Computing and Artificial Intelligence (AI) Applications for...

Area of Science:

• Healthcare Informatics
• Cybersecurity
• Cloud Computing

Background:

• Cloud computing and AI offer EQA providers scalability and cost efficiency.
• Adoption of these technologies presents significant cybersecurity and data privacy challenges.

Purpose of the Study:

• To identify and analyze cybersecurity risks associated with cloud computing and AI in EQA.
• To develop a risk-focused framework for mitigating these challenges.

Main Methods:

• Systematic literature review on healthcare cloud computing cybersecurity.
• Expert consultations in bioinformatics and cybersecurity.
• Analysis of real-world hacking incidents targeting EQA organizations.

Main Results:

• Ten key cybersecurity challenges were identified, including data breaches, regulatory non-compliance (HIPAA, GDPR), data sovereignty issues, and insider threats.
• Vulnerabilities in shared infrastructure, cloud provider security, and applications were highlighted.
• Limited visibility, control, and complexity of cloud security management pose significant risks.

Conclusions:

• EQA providers must implement robust security practices and ensure regulatory compliance for cloud and AI adoption.
• Continuous monitoring and proactive cybersecurity strategies are essential for safeguarding laboratory data.
• Effective risk management is critical for maintaining operational continuity and accreditation.