What does audit trails enable in AI security monitoring?

What does audit trails enable in AI security monitoring?

• A. Accountability And Traceability
• B. Increased Compute
• C. Faster Model Training
• D. More Data Duplication

Answer: (A)

In AI security monitoring, audit trails are the records of who did what, when, and with which data or models. They enable accountability by tying actions to specific actors or systems, so you can determine responsibility for security events. They also provide traceability by offering a reconstructible sequence of events—data access, model versions, configuration changes, and other actions—so investigators can understand what happened and how it unfolded. This is essential for incident response, forensic analysis, and regulatory compliance. The other options don’t reflect what audit trails are designed to do; audit logs aren’t about increasing compute, speeding up training, or creating data duplication. They’re about knowing who did what and when, and tracing the sequence of events.

In AI security monitoring, audit trails are the records of who did what, when, and with which data or models. They enable accountability by tying actions to specific actors or systems, so you can determine responsibility for security events. They also provide traceability by offering a reconstructible sequence of events—data access, model versions, configuration changes, and other actions—so investigators can understand what happened and how it unfolded. This is essential for incident response, forensic analysis, and regulatory compliance. The other options don’t reflect what audit trails are designed to do; audit logs aren’t about increasing compute, speeding up training, or creating data duplication. They’re about knowing who did what and when, and tracing the sequence of events.