Minimising risks associated with LLMs: AI offers enormous potential, but requires rigorous data masking!

How companies mitigate PII risks with LLMs: Large language models (LLMs) open up new possibilities in data analysis and automation – but they also pose significant data protection risks. Of particular concern is the handling of personally identifiable information (PII), which may inadvertently appear in training data, prompts or model responses.

Three main risks arise when using LLMs:

1. Data leaks: Models can reproduce sensitive information
2. Insecure inputs: Prompts often contain unprotected PII
3. Regulatory requirements: Regulations such as the GDPR require strict controls

An effective security strategy must therefore encompass several levels:

• Before training: Identify and mask sensitive data
• During use: Sanitise inputs
• After processing: Check and filter outputs
• Documentation: Provide audit logs for compliance

Modern solutions such as IRI DarkShield rely on intelligent methods to protect data without compromising its usability:

1. Context-based detection of sensitive content
2. Consistent pseudonymisation or tokenisation
3. Protection of structured and unstructured data
4. Real-time processing for streaming and AI applications

Conclusion: The secure use of LLMs requires more than traditional security measures. A comprehensive approach that identifies and protects sensitive data whilst preserving its analytical value is crucial. This is how innovation and data protection can be successfully combined.

Efficiency meets experience: For more than four decades, our software solutions have been supporting companies in data management and data protection – technologically leading, reliable in productive use and applicable across all industries.

In use since 1978: Numerous well-known companies, service providers, financial institutions and state and federal authorities are among our long-standing customers.

Maximum compatibility: Our software supports both classic mainframe platforms (Fujitsu BS2000/OSD, IBM z/OS, z/VSE, z/Linux) and modern open system environments such as Linux, UNIX derivatives and Windows.