公开(公告)号：US11429891B2

公开(公告)日：2022-08-30

申请号：US15914057

申请日：2018-03-07

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Yali Liu ,  Jin Wang ,  Zhengye Liu ,  Bruce Schine

IPC: G06N20/00 ,  H04N21/4408 ,  H04N21/44 ,  H04L9/40

Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.

公开(公告)号：US20220351084A1

公开(公告)日：2022-11-03

申请号：US17868465

申请日：2022-07-19

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Yali Liu ,  Jin Wang ,  Zhengye Liu ,  Bruce Schine

IPC: G06N20/00 ,  H04N21/4408 ,  H04N21/44 ,  H04L9/40

Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.

公开(公告)号：US11699103B2

公开(公告)日：2023-07-11

申请号：US17868465

申请日：2022-07-19

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Yali Liu ,  Jin Wang ,  Zhengye Liu ,  Bruce Schine

IPC: G06N20/00 ,  H04N21/4408 ,  H04N21/44 ,  H04L9/40

CPC classification number: G06N20/00 ,  H04L63/0428 ,  H04N21/44008 ,  H04N21/4408

Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.

公开(公告)号：US20190279113A1

公开(公告)日：2019-09-12

申请号：US15914057

申请日：2018-03-07

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Yali Liu ,  Jin Wang ,  Zhengye Liu ,  Bruce Schine

IPC: G06N99/00 ,  H04L29/06 ,  H04N21/44 ,  H04N21/4408

Abstract: Aspects of the subject disclosure may include, for example, a processing system that performs operations including collecting encrypted network traffic flow data from user interaction with an application, deriving a first set of traffic feature vectors from the encrypted network traffic flow data collected, training a machine learning algorithm on the first set of traffic feature vectors to classify each traffic feature vector in the first set of traffic feature vectors as associated with a type of the application or not associated with the type of the application, and classifying whether an encrypted network traffic flow as the type of the application by applying the machine learning algorithm to a traffic feature vector of the encrypted network traffic flow. Other embodiments are disclosed.