Today, in collaboration with international partners, we have released new advice on best practices for securing data throughout the artificial intelligence (AI) system lifecycle.
The publication provides essential data security guidance for organisations that develop and/or use AI systems, including businesses, government and critical infrastructure. It highlights the importance of data security in ensuring the accuracy and integrity of AI outcomes, and presents an in-depth examination of 3 areas of data security risks in AI systems: data supply chain, maliciously modified (poisoned) data, and data drift.
General best practices to secure data in AI systems involve:
- data encryption
- digital signatures
- data provenance tracking
- secure storage
- trusted infrastructure.
Read the full publication to learn more about AI data security.