公开(公告)号：US11671446B2

公开(公告)日：2023-06-06

申请号：US17120050

申请日：2020-12-11

Applicant: Google LLC

Inventor： Francois Pepin ,  Andre Lloyd Perlee Harder ,  Prajakta Joshi ,  Amitabha Roy ,  Saila Talagadadeevi ,  Emil Kiner ,  Chia-Tung Kuo ,  Jiayu Ye

IPC: H04L9/40 ,  H04L41/142

CPC classification number: H04L63/1458 ,  H04L41/142 ,  H04L63/0263 ,  H04L63/1416

Abstract: A method for mitigating network abuse includes obtaining a first set of network traffic messages of network traffic currently received by a network service and determining, via a first model, whether network abuse is occurring based on the first set of network traffic messages. When the network abuse is occurring, the method includes obtaining a second set of current network traffic messages. The method also includes, for each network traffic message in the second set of network traffic messages, labeling, via a second model, the network traffic message as an abusing network traffic message or a non-abusing network traffic message. The method also includes generating, via a third model, at least one network traffic rule. Each network traffic rule, when implemented, reduces an effect of the abusing network traffic messages.

公开(公告)号：US20240370717A1

公开(公告)日：2024-11-07

申请号：US18313189

申请日：2023-05-05

Applicant: Google LLC

Inventor： Qifei Wang ,  Yicheng Fan ,  Wei Xu ,  Jiayu Ye ,  Lu Wang ,  Chuo-Ling Chang ,  Dana Alon ,  Erik Nathan Vee ,  Hongkun Yu ,  Matthias Grundmann ,  Shanmugasundaram Ravikumar ,  Andrew Stephen Tomkins

IPC: G06N3/08

Abstract: A method for a cross-platform distillation framework includes obtaining a plurality of training samples. The method includes generating, using a student neural network model executing on a first processing unit, a first output based on a first training sample. The method also includes generating, using a teacher neural network model executing on a second processing unit, a second output based on the first training sample. The method includes determining, based on the first output and the second output, a first loss. The method further includes adjusting, based on the first loss, one or more parameters of the student neural network model. The method includes repeating the above steps for each training sample of the plurality of training samples.

公开(公告)号：US20230308476A1

公开(公告)日：2023-09-28

申请号：US18314532

申请日：2023-05-09

Applicant: Google LLC

Inventor： Francois Pepin ,  Andre Lloyd Perlee Harder ,  Prajakta Joshi ,  Amitabha Roy ,  Saila Talagadadeevi ,  Emil Kiner ,  Chia-Tung Kuo ,  Jiayu Ye

IPC: H04L9/40 ,  H04L41/142

CPC classification number: H04L63/1458 ,  H04L41/142 ,  H04L63/0263 ,  H04L63/1416

Abstract: A method for mitigating network abuse includes obtaining a first set of network traffic messages of network traffic currently received by a network service and determining, via a first model, whether network abuse is occurring based on the first set of network traffic messages. When the network abuse is occurring, the method includes obtaining a second set of current network traffic messages. The method also includes, for each network traffic message in the second set of network traffic messages, labeling, via a second model, the network traffic message as an abusing network traffic message or a non-abusing network traffic message. The method also includes generating, via a third model, at least one network traffic rule. Each network traffic rule, when implemented, reduces an effect of the abusing network traffic messages.

公开(公告)号：US20220191242A1

公开(公告)日：2022-06-16

申请号：US17120050

申请日：2020-12-11

Applicant: Google LLC

Inventor： Francois Pepin ,  Andre Lloyd Perlee Harder ,  Prajakta Joshi ,  Amitabha Roy ,  Saila Talagadadeevi ,  Emil Kiner ,  Chia- Tung Kuo ,  Jiayu Ye

IPC: H04L29/06 ,  H04L12/24

Abstract: A method for mitigating network abuse includes obtaining a first set of network traffic messages of network traffic currently received by a network service and determining, via a first model, whether network abuse is occurring based on the first set of network traffic messages. When the network abuse is occurring, the method includes obtaining a second set of current network traffic messages. The method also includes, for each network traffic message in the second set of network traffic messages, labeling, via a second model, the network traffic message as an abusing network traffic message or a non-abusing network traffic message. The method also includes generating, via a third model, at least one network traffic rule. Each network traffic rule, when implemented, reduces an effect of the abusing network traffic messages.