公开(公告)号：US11410047B2

公开(公告)日：2022-08-09

申请号：US16237114

申请日：2018-12-31

Applicant: PAYPAL, INC.

Inventor： Liron Florens Ben Kimon ,  Michael Dymshits ,  Albert Zelmanovitch ,  Dan Ayash

IPC: G06N3/08 ,  G06Q20/38

Abstract: Systems and methods for anomaly detection includes accessing first data comprising a plurality of historical reversion transactions. A plurality of legitimate transactions are determined from the plurality of historical reversion transactions. An autoencoder is trained using the plurality of legitimate transactions to generate a trained autoencoder capable of measuring a given transaction for similarity to the plurality of legitimate transactions. A first reconstructed transaction is generated by the trained autoencoder using a first transaction. The first transaction is determined to be anomalous based on a reconstruction difference between the first transaction and the first reconstructed transaction.

公开(公告)号：US20200210849A1

公开(公告)日：2020-07-02

申请号：US16237114

申请日：2018-12-31

Applicant: PAYPAL, INC.

Inventor： Liron Florens Ben Kimon ,  Michael Dymshits ,  Albert Zelmanovitch ,  Dan Ayash

IPC: G06N3/08 ,  G06Q20/38

Abstract: Systems and methods for anomaly detection includes accessing first data comprising a plurality of historical reversion transactions. A plurality of legitimate transactions are determined from the plurality of historical reversion transactions. An autoencoder is trained using the plurality of legitimate transactions to generate a trained autoencoder capable of measuring a given transaction for similarity to the plurality of legitimate transactions. A first reconstructed transaction is generated by the trained autoencoder using a first transaction. The first transaction is determined to be anomalous based on a reconstruction difference between the first transaction and the first reconstructed transaction.