DISTRIBUTED TRAINING OF A MACHINE LEARNING MODEL TO DETECT NETWORK ATTACKS IN A COMPUTER NETWORK

摘要

Training method to train machine learning model (e.g., neural network) used to identify attacks in a network (e.g., denial of service). A first data set is received by a network device that is indicative of the statuses of a plurality of network devices when a type of network attack is not present. A second data set is also received that is indicative of the statuses of the plurality of network devices when the type of network attack is present. At least one of the plurality simulates the type of network attack by operating as an attacking node. A machine learning model is trained using the first and second data set to identify the type of network attack. A real network attack is then identified using the trained machine learning model. Application in Low Power and Lossy Networks.