The correct options are False acceptance rate, Crossover error rate, and False rejection rate.

False acceptance rate measures the proportion of impostors who are incorrectly granted access. It is a standard scalar metric for biometric systems and it quantifies the system risk of allowing unauthorized users.

False rejection rate measures the proportion of genuine users who are incorrectly denied access. It is the complementary error to the acceptance side and it quantifies the user convenience impact of the system.

Crossover error rate is the operating point where the False acceptance rate and the False rejection rate are equal. It is commonly reported as a single number that summarizes the trade off between security and usability and lower values indicate better overall biometric performance.

Detection error tradeoff is not one of the three scalar metrics. It usually refers to a DET curve which visualizes the trade off between false acceptances and false rejections across thresholds rather than providing a single performance number.

Negative error rate is not a standard biometric performance term. It may be a misnomer for a false negative concept, but the standard terms used in biometric evaluation are False rejection rate for false negatives and False acceptance rate for false positives.

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