公开(公告)号：US10771488B2

公开(公告)日：2020-09-08

申请号：US15949198

申请日：2018-04-10

Applicant: Cisco Technology, Inc.

Inventor： Saurabh Verma ,  Manjula Shivanna ,  Gyana Ranjan Dash ,  Antonio Nucci

IPC: H04L29/06 ,  G06N3/08

Abstract: In one embodiment, a device receives sensor data from a plurality of nodes in a computer network. The device uses the sensor data and a graph that represents a topology of the nodes in the network as input to a graph convolutional neural network. The device provides an output of the graph convolutional neural network as input to a convolutional long short-term memory recurrent neural network. The device detects an anomaly in the computer network by comparing a reconstruction error associated with an output of the convolutional long short-term memory recurrent neural network to a defined threshold. The device initiates a mitigation action in the computer network for the detected anomaly.

公开(公告)号：US20190312898A1

公开(公告)日：2019-10-10

申请号：US15949198

申请日：2018-04-10

Applicant: Cisco Technology, Inc.

Inventor： Saurabh Verma ,  Manjula Shivanna ,  Gyana Ranjan Dash ,  Antonio Nucci

IPC: H04L29/06 ,  G06N3/08

Abstract: In one embodiment, a device receives sensor data from a plurality of nodes in a computer network. The device uses the sensor data and a graph that represents a topology of the nodes in the network as input to a graph convolutional neural network. The device provides an output of the graph convolutional neural network as input to a convolutional long short-term memory recurrent neural network. The device detects an anomaly in the computer network by comparing a reconstruction error associated with an output of the convolutional long short-term memory recurrent neural network to a defined threshold. The device initiates a mitigation action in the computer network for the detected anomaly.