De-linked data is information that has been processed so direct identity markers, such as a user ID, account email, or profile key, are removed or separated before further use. In security and privacy workflows, this lets teams review, analyze, or train on data without exposing the record to the same identity as the original source. It is a common control in AI systems, logging pipelines, and internal investigations where the content matters more than the person attached to it.
In cyber security, de-linking helps reduce the impact of insider misuse, access abuse, and accidental overexposure. For example, a support transcript can be reviewed in de-linked form so analysts see the conversation but not the customer account. However, de-linking is not the same as full anonymization: attackers may still re-identify data by combining it with other details, a risk known as linkage attack. Strong defenses pair de-linking with access controls, minimization, and limited retention.