IoT Attack Detection Using LSTM Model

It is suggested in this paper that an LSIM model be used to find DDoS attacks, which usually involve patterns of bad traffic that happen over time. The idea for the model comes from the fact that bad IoTdevices often leave traces in network traffic data that can be used to find them. This is what the LSIM model needs to be done before it can spot attacks in real-time. An IoTattack dataset was used to test how well the suggested method works. What the test showed was that the suggested method worked well to find attacks. The suggested method can likely be used to find attacks on the Internet of Things. It's simple to set up and can stop many types of break-ins. This method will only work, though, if the training data are correct.LSIMmodel could be used to find attack detection who are breaking into the Internet of Things. Long short-term memory (LSIM) models are a type of AI that can find trends in data that have been collected over time. The LSIM model learns the difference patterns in network traffic data that are normal and patterns that show an attack. The proposed method to see how well it worked and found that it could achieve a precision of 99.4%.