Addressing contemporary threats in anonymised healthcare data using privacy engineering

Area of Science:

• Health Informatics
• Cybersecurity
• Artificial Intelligence

Background:

• Increasing cyber-attacks and data breaches in healthcare pose significant risks to sensitive patient information.
• Emerging artificial intelligence (AI) and data analytics techniques enable the inference of sensitive characteristics from non-personally identifiable information (non-PII) data.
• The combination of AI, analytics, and online repositories creates novel privacy vulnerabilities in healthcare.

Purpose of the Study:

• To identify and discuss current and emerging privacy threats in the healthcare data landscape.
• To explore privacy engineering solutions and the strategic selection of privacy-enhancing technologies (PETs).
• To address the need for robust data protection in the context of evolving data flows and AI integration.

Main Methods:

• Review of current literature on healthcare cybersecurity threats and AI-driven data inference.
• Analysis of privacy risks associated with combining disparate online data sources and advanced analytics.
• Framework development for selecting appropriate privacy-enhancing technologies based on specific healthcare use cases.

Main Results:

• Demonstration of how sensitive individual characteristics can be inferred without direct access to personal identifiable information (PII).
• Identification of key privacy threats stemming from the convergence of AI, big data analytics, and accessible online repositories.
• Guidance on selecting and implementing effective privacy-enhancing technologies tailored to diverse healthcare data scenarios.

Conclusions:

• The evolving threat landscape necessitates proactive privacy engineering and the adoption of advanced privacy-enhancing technologies in healthcare.
• Effective privacy solutions must account for the entire data lifecycle, including dynamic data flows.
• A strategic approach to selecting and implementing privacy measures is crucial for safeguarding sensitive health information in the age of AI.