Amazon Technologies, Inc.

Zhen Han

Rui Zhao

Gerard Guy Medioni

Manoj Aggarwal

Brad Musick

A person may attempt to gain access to a facility via transaction data, such as images of a hand of the person or other identifying information as acquired by an input device. Possible fraud may be detected by comparing the transaction data with previously stored exclusion data. The exclusion data may include known bad data or synthetic trained data for detecting possible fraud. If the biometric input matches or is similar to the exclusion data, possible fraud is detected and the person is prompted for additional data. The reply data acquired from the person is compared with the exclusion data to determine if possible fraud is still detected. If so, additional prompts are presented to the person until the reply data provides enough confidence of no fraud or until the transaction is terminated.

System for detecting and mitigating fraudulent biometric input

Biometric input, such as images of a hand obtained by a biometric input device, may be used to identify a person. An attacker may attempt to gain access by presenting false biometric data with an artificial biometric model, such as a fake hand. During a suspected attack, the attacker is prompted for additional data. For example, email address, telephone number, payment information, and so forth. This provides additional information about the attack while prolonging the time spent by the attacker on the attack. Information explicitly indicating failure is delayed or not presented at all. Data associated with an attack is placed into an exclusion list and further analyzed to recognize and mitigate future attacks. A subsequent attempt that corresponds to exclusion data proceeds with presenting prompts, gathering further information and consuming more of the attacker's time and resources.

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Issaquah, WA, United States of America

Zhen Han