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APPLICATION OF TRAINED ARTIFICIAL INTELLIGENCE PROCESSES TO ENCRYPTED DATA WITHIN A DISTRIBUTED COMPUTING ENVIRONMENT

机译:经过训练的人工智能过程在分布式计算环境中对加密数据的应用

摘要

The disclosed embodiments include computer-implemented processes that predict a credit score for a customer in real-time based on an application of a trained machine-learning or artificial-intelligence process to encrypted event data at a third-party computing cluster. For example, an apparatus may transmit encrypted event data to a third-party computing system. The third-party computing system may apply a trained artificial intelligence process to encrypted feature data that includes the encrypted event data, and the apparatus may receive, from the third-party computing system, encrypted output data representative of a predicted credit score during at least one temporal interval. The apparatus may decrypt the encrypted output data using a homomorphic decryption key, and transmit a notification that includes the decrypted output data to a device. An application program executed at the device may present a graphical representation of at least a portion of the decrypted output data within a digital interface.
机译:所公开的实施例包括计算机实现的过程,这些过程基于对第三方计算集群上的加密事件数据应用经过训练的机器学习或人工智能过程,实时预测客户的信用评分。例如,设备可以向第三方计算系统发送加密的事件数据。第三方计算系统可以对包括加密事件数据的加密特征数据应用经过训练的人工智能过程,并且设备可以从第三方计算系统接收代表至少一个时间间隔内的预测信用评分的加密输出数据。该装置可以使用同态解密密钥解密加密的输出数据,并将包括解密的输出数据的通知发送到设备。在设备上执行的应用程序可以在数字接口内呈现解密输出数据的至少一部分的图形表示。

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