The Australian Securities Directorate (ASD), in partnership with global collaborators, has released new recommendations on optimal practices for safeguarding data throughout the lifecycle of artificial intelligence (AI) and machine learning (ML) systems.
The cybersecurity recommendations emphasize the significance of data security in maintaining the accuracy and integrity of AI results and detail potential risks that may arise from data integrity problems at various phases of AI development and implementation.
Additionally, it offers crucial data security advice for organizations that create and/or utilize AI systems, particularly those that integrate AI into their operations, focusing on the protection of sensitive, proprietary, or mission-critical information.
ASD principles presented aim to establish a “strong” foundation for securing AI data and ensuring the dependability and precision of AI-generated results.
The ASD asserts that data security is critically important in the development and operation of AI systems.
As organizations across different sectors increasingly depend on AI-generated results, data security becomes vital for preserving accuracy, reliability, and integrity.
The guidance outlined in the ASD’s cybersecurity information sheet (CIS) presents a “strong strategy for securing AI data and tackling the risks linked to the data supply chain, malicious data, and data drift.”
Data security is a constantly changing domain, and ongoing vigilance and adaptation are essential for keeping ahead of new threats and vulnerabilities, as highlighted by the CIS.
ASD recommended practices promote the highest levels of data security in AI while aiding in the assurance of the accuracy and integrity of AI-generated results.
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