Data Privacy / Data Security

Data Security refers to the totality of technical and regulatory measures that protect the confidentiality, integrity, and availability of information during the application of artificial intelligence. It is of particular importance during model training and use, preventing sensitive corporate or personal data from leaking into public models (e.g., through prompt injection attacks or accidental data sharing). Proper encryption, access management, and the use of isolated environments are prerequisites for enterprise-level AI adaptation. Data Privacy is the area of information security dealing with the regulation of the collection, storage, use, and sharing of personal and sensitive data. In the AI context, this includes ensuring that data used in model training does not violate individuals' privacy, and that generated outputs do not contain re-identifiable information. Adhering to strict data privacy principles (such as GDPR) is essential for maintaining user trust and legal compliance, especially during the enterprise integration of cloud-based AI services.