Amazon Technologies, Inc.

Brad Musick

Gerard Guy Medioni

Manoj Aggarwal

Rui Zhao

Zhen Han

Prithviraj Banerjee

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

Techniques for an identity-verification system to analyze image data representing palms of users using a segmented, characteristic-based approach. The system may compare palm-feature data representing characteristics of a palm of a user (or 'query palm') with stored palm-feature data of palms for user profiles (or 'stored palms'). For instance, the system may identify characteristics of the query palm having salient or discriminative features, and compare palm-feature data for those discriminative characteristics to palm-feature data representing corresponding characteristics of stored palms of enrolled users. Additionally, the system may compare characteristics of the query palm with corresponding characteristics of stored palms until the system is confident that the query palm corresponds to a stored palm of a user profile. By performing simpler characteristic-by-characteristic sameness verification tasks, the system may reduce the amount of time and computing resources utilized to verify an identity of a user as opposed to top-level, palm-identity verification.

Utilizing sensor data for automated user identification

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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Brad Musick