公开(公告)号：US12192222B2

公开(公告)日：2025-01-07

申请号：US18301862

申请日：2023-04-17

Applicant: KOUNT INC.

Inventor： Joshua Michael Johnston ,  Matthew Lewis Jones ,  Nathan Daniel Monnig ,  Divyanshu Rohit Murli

IPC: H04L9/40 ,  G06F21/55

Abstract: A method described herein involves various operations directed toward network security. The operations include accessing transaction data describing network traffic associated with a web server during an interval. Based on a count of new transactions involving an online entity during the interval according to the transaction data, a short-term trend is determined for the online entity. The operations further include applying exponential smoothing to a history of transactions of the online entity to compute a long-term trend for the online entity. Based on a comparison between the short-term trend and the long-term trend for the online entity, an anomaly is detected with respect to the online entity in the network traffic associated with the web server. Responsive to detecting the anomaly, an access control is implemented between the online entity and the web server.

公开(公告)号：US11658994B2

公开(公告)日：2023-05-23

申请号：US17754854

申请日：2021-07-14

Applicant: KOUNT INC.

Inventor： Joshua Michael Johnston ,  Matthew Lewis Jones ,  Nathan Daniel Monnig ,  Divyanshu Rohit Murli

IPC: H04L9/40 ,  G06F21/55

CPC classification number: H04L63/1425 ,  H04L63/1433 ,  H04L63/1458

Abstract: A method described herein involves various operations directed toward network security. The operations include accessing transaction data describing network traffic associated with a web server during an interval. Based on a count of new transactions involving an online entity during the interval according to the transaction data, a short-term trend is determined for the online entity. The operations further include applying exponential smoothing to a history of transactions of the online entity to compute a long-term trend for the online entity. Based on a comparison between the short-term trend and the long-term trend for the online entity, an anomaly is detected with respect to the online entity in the network traffic associated with the web server. Responsive to detecting the anomaly, an access control is implemented between the online entity and the web server.