Privacy Leakage

Mitigation strategy

- Prioritize the implementation of advanced privacy-preserving techniques, such as Differential Privacy and rigorous Data Splitting, to obfuscate sensitive details within training datasets and prevent their unintentional reconstruction or leakage into the generated model output. - Deploy robust Data Loss Prevention (DLP) solutions and Anti-Data Exfiltration (ADX) technology to actively monitor and block the transmission of sensitive personal information contained within the generated content across network boundaries and user endpoints in real-time. - Establish and strictly enforce the principle of least privilege through Role-Based Access Controls (RBAC) and Multi-Factor Authentication (MFA), restricting access to the AI model's training data, internal configuration, and output logs to only the minimum set of authorized personnel required for operational duties.