公开(公告)号：US20240396912A1

公开(公告)日：2024-11-28

申请号：US18672516

申请日：2024-05-23

Applicant: AJOU UNIVERSITY INDUSTRY-ACADEMIC COOPERATION FOUNDATION

Inventor： Jin KWAK ,  Deukhun KIM ,  Lelisa Adeba JILCA ,  Insu JUNG

IPC: H04L9/40

Abstract: A network intrusion detection system includes: a data collection unit configured to obtain a dataset for training a plurality of machine learning-based heterogeneous models included in the network intrusion detection system; a clustering module configured to cluster data points included in the obtained dataset; a routing module configured to selectively input the data points into at least one of the plurality of models based on a result of the clustering; and a model training unit configured to define a loss function based on a reconstruction loss of each of the at least one model for an input data point, and perform an update of each of the at least one model so that the defined loss function is minimized, wherein the model training unit sets an anomaly threshold for each of the at least one model based on loss distribution of reconstruction losses for the data points.

公开(公告)号：US20240179155A1

公开(公告)日：2024-05-30

申请号：US18397144

申请日：2023-12-27

Applicant: AJOU UNIVERSITY INDUSTRY-ACADEMIC COOPERATION FOUNDATION

Inventor： Jin KWAK ,  Deuk Hun KIM ,  Lelisa Adeba JILCA

IPC: H04L9/40

CPC classification number: H04L63/1416

Abstract: A network security situation assessment method of a network system includes: obtaining network traffic of the network system; detecting an attack on the network system from the obtained network traffic; identifying the detected attack; analyzing a possibility of an attack and an impact of an attack on the network system based on results of the detecting and identifying of the attack; and assessing a network situation of the network system based on a result of the analyzing, wherein the detecting of the attack on the network system includes detecting the attack from the network traffic using deep learning-based first model and second model.