公开(公告)号：US20240311614A1

公开(公告)日：2024-09-19

申请号：US18610191

申请日：2024-03-19

Applicant: PayPal, Inc.

Inventor： Xiaodong Yu ,  Jiazheng Zhang ,  Jiyi Zhang ,  Quan Jin Ferdinand Tang ,  Shanshan Peng ,  Yuzhen Zhuo ,  Hong Qian ,  Runmin Wen

IPC: G06N3/045 ,  G06N3/08 ,  G06T7/11 ,  G06T7/70

CPC classification number: G06N3/045 ,  G06N3/08 ,  G06T7/11 ,  G06T7/70 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20132 ,  G06T2210/12

Abstract: Systems and/or techniques for facilitating image forgery detection via headpose estimation may include a system that can receive a document from a client device. The system can identify, by executing a first trained machine learning model, an object that is depicted in the document. The system can determine, by executing a second trained machine learning model, a pose of the object. The system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. The system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.

公开(公告)号：US11907658B2

公开(公告)日：2024-02-20

申请号：US17308931

申请日：2021-05-05

Applicant: PayPal, Inc.

Inventor： Zhe Chen ,  Hewen Wang ,  Yuzhen Zhuo ,  Solomon kok how Teo ,  Shanshan Peng ,  Quan Jin Ferdinand Tang ,  Serafin Trujillo ,  Kenneth Bradley Snyder ,  Mandar Ganaba Gaonkar ,  Omkumar Mahalingam

IPC: G06F40/279 ,  G06F21/55 ,  G06F21/56 ,  G06F40/284 ,  G06F40/30 ,  G06F18/2321 ,  G06F18/2415

CPC classification number: G06F40/284 ,  G06F18/2321 ,  G06F18/2415 ,  G06F40/30

Abstract: Systems and methods for user-agent anomaly detection are disclosed. In one embodiment, a user-agent string may be embedded into a numerical data vector representation using a sentence embedding algorithm (e.g., FastText). A predictive score may be calculated based on the numerical data vector representation and using a probability distribution function model that models a likelihood of occurrence of the observed user-agent based on patterns learned from historic payload data (e.g., a Gaussian Mixture Model). The predictive score may be compared to a threshold and, based on the comparison, it may be determined whether the user-agent is fraudulent.

公开(公告)号：US11893816B2

公开(公告)日：2024-02-06

申请号：US17458090

申请日：2021-08-26

Applicant: PAYPAL, INC.

Inventor： Shanshan Peng ,  Khine Phyo Yar ,  Yuzhen Zhuo

IPC: G06V30/18 ,  G06T7/12 ,  G06V10/94 ,  G06V30/40

CPC classification number: G06V30/18 ,  G06T7/12 ,  G06V10/955 ,  G06V30/40 ,  G06T2207/10004

Abstract: Methods and systems are presented for detecting a boundary of a document within a digital image. Upon receiving an image, the image is converted into a binary image. One or more kernel-based transformations are performed on the binary image using a horizontal kernel and a vertical kernel. A plurality of edges are identified based on the one or more kernel-based transformations. The plurality of edges includes a plurality of horizontal edges and a plurality of vertical edges. Multiple quadrilaterals are constructed using different combinations of horizontal edges and vertical edges from the plurality of edges. A particular quadrilateral is selected from the multiple quadrilaterals based on how well the edges fit the perimeters of the quadrilaterals. The selected quadrilateral is used to define a boundary of the document within the digital image.

公开(公告)号：US11689526B2

公开(公告)日：2023-06-27

申请号：US16689045

申请日：2019-11-19

Applicant: PAYPAL, INC.

Inventor： Xiaodong Yu ,  Quan Jin Ferdinand Tang ,  Jiyi Zhang ,  Yuzhen Zhuo

IPC: H04L9/40 ,  G06Q20/40 ,  G06N3/08 ,  G06V40/16 ,  G06V10/764 ,  G06V10/80 ,  G06V10/82 ,  G06V10/24

CPC classification number: H04L63/0861 ,  G06N3/08 ,  G06Q20/40145 ,  G06V10/24 ,  G06V10/764 ,  G06V10/809 ,  G06V10/82 ,  G06V40/172

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for user identification using Artificial Intelligence, Machine Learning, and data analytics. In one embodiment, a verification system and method is introduced that can provide user authentication using parallel modeling for face identification. The verification system used includes a face identification module for use in the identification and verification using parallel processing of a received image with a claimed identity. The parallel processing includes an ensemble of machine learning models processed in parallel for optimal performance.

公开(公告)号：US20230005122A1

公开(公告)日：2023-01-05

申请号：US17374439

申请日：2021-07-13

Applicant: PayPal, Inc.

Inventor： Shanshan Peng ,  Jiazheng Zhang ,  Jiyi Zhang ,  Quan Jin Ferdinand Tang ,  Xiaodong Yu ,  Yuzhen Zhuo ,  Hong Qian ,  Zhe Chen ,  Runmin Wen

IPC: G06T7/00 ,  G06N20/20 ,  G06K9/62

Abstract: Systems and/or techniques for facilitating image forgery detection via pixel-metadata consistency analysis are provided. In various embodiments, a system can receive an electronic image from a client device. In various cases, the system can obtain a pixel vector and/or an image metadata vector that correspond to the electronic image. In various aspects, the system can determine whether the electronic image is authentic or forged, based on analyzing the pixel vector and the image metadata vector via at least one machine learning model.

公开(公告)号：US20210150534A1

公开(公告)日：2021-05-20

申请号：US16689045

申请日：2019-11-19

Applicant: PAYPAL, INC.

Inventor： Xiaodong Yu ,  Quan Jin Ferdinand Tang ,  Jiyi Zhang ,  Yuzhen Zhuo

IPC: G06Q20/40 ,  G06K9/00 ,  H04L29/06 ,  G06N3/08

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for user identification using Artificial Intelligence, Machine Learning, and data analytics. In one embodiment, a verification system and method is introduced that can provide user authentication using parallel modeling for face identification. The verification system used includes a face identification module for use in the identification and verification using parallel processing of a received image with a claimed identity. The parallel processing includes an ensemble of machine learning models processed in parallel for optimal performance.

公开(公告)号：US12118560B2

公开(公告)日：2024-10-15

申请号：US17651081

申请日：2022-02-15

Applicant: PayPal, Inc.

Inventor： Zhe Chen ,  Hewen Wang ,  Solomon Kok How Teo ,  Yuzhen Zhuo ,  Quan Jin Ferdinand Tang ,  Mandar Ganaba Gaonkar ,  Omkumar Mahalingam ,  Kenneth Bradley Snyder

IPC: G06Q40/00 ,  G06F3/01 ,  G06F3/03 ,  G06F18/21 ,  G06N20/20 ,  G06Q20/40

CPC classification number: G06Q20/4016 ,  G06F3/017 ,  G06F3/0304 ,  G06F18/217 ,  G06N20/20 ,  G06Q20/40145

Abstract: Techniques are disclosed relating to determining whether to authorize a requested action based on whether an entity is an automated computer. In some embodiments, a computer system tracks, at a user interface of a computing device, a sequence of pointer movements. The computer system maps, based on coordinate locations of pointer movements in the sequence, respective movements in the sequence to a plurality of functional areas. Based on the mapping, the computer system generates a movement graph and determines, based on the movement graph, whether an entity associated with the sequence of pointer movements is an automated computer. In response to receiving a request to authorize an action at the computing device, the computer system generates, based on the determining, an authorization decision for the action and transmits the authorization decision to the computing device. Determining whether the entity is an automated computer may advantageously prevent fraudulent activity.

公开(公告)号：US20230419715A1

公开(公告)日：2023-12-28

申请号：US17850602

申请日：2022-06-27

Applicant: PAYPAL, INC.

Inventor： Jiazheng Zhang ,  Yuzhen Zhuo ,  Jiyi Zhang

IPC: G06V30/418 ,  G06V30/413 ,  G06V30/42

CPC classification number: G06V30/418 ,  G06V30/413 ,  G06V30/42

Abstract: Methods and systems are presented for detecting physical tampering on a document based on analyzing an image of the document. When the image of the document is obtained, multiple contours are identified in the image based on pixel characteristics of the image. Dimension attributes of the contours are determined. Contours that are determined to correspond to borders or texts of the documents based on the dimension attributes are eliminated. A second text detection process based on a polygon method is performed on at least one remaining contour to determine whether the at least one remaining contour links multiple text elements together. The document is determined to have been physically manipulated when at least on contour remains in the image.

公开(公告)号：US20230061009A1

公开(公告)日：2023-03-02

申请号：US17458090

申请日：2021-08-26

Applicant: PAYPAL, INC.

Inventor： Shanshan Peng ,  Khine Phyo Yar ,  Yuzhen Zhuo

IPC: G06K9/46 ,  G06K9/00 ,  G06T7/12

Abstract: Methods and systems are presented for detecting a boundary of a document within a digital image. Upon receiving an image, the image is converted into a binary image. One or more kernel-based transformations are performed on the binary image using a horizontal kernel and a vertical kernel. A plurality of edges are identified based on the one or more kernel-based transformations. The plurality of edges includes a plurality of horizontal edges and a plurality of vertical edges. Multiple quadrilaterals are constructed using different combinations of horizontal edges and vertical edges from the plurality of edges. A particular quadrilateral is selected from the multiple quadrilaterals based on how well the edges fit the perimeters of the quadrilaterals. The selected quadrilateral is used to define a boundary of the document within the digital image.

公开(公告)号：US20220318597A1

公开(公告)日：2022-10-06

申请号：US17236085

申请日：2021-04-21

Applicant: PayPal, Inc.

Inventor： Xiaodong Yu ,  Jiazheng Zhang ,  Jiyi Zhang ,  Quan Jin Ferdinand Tang ,  Shanshan Peng ,  Yuzhen Zhuo ,  Hong Qian ,  Runmin Wen

IPC: G06N3/04 ,  G06N3/08 ,  G06T7/70 ,  G06T7/11

Abstract: Systems and/or techniques for facilitating image forgery detection via headpose estimation are provided. In various embodiments, a system can receive a document from a client device. In various cases, the system can identify, by executing a first trained machine learning model, an object that is depicted in the document. In various instances, the system can determine, by executing a second trained machine learning model, a pose of the object. In various aspects, the system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. In various embodiments, the system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.