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Design and Implementation of deep learning algorithms for anomaly based intrusion detection for internet of things (iot)

. Vibhore wahi, Sarthak Yadav, Yash Thenuia and Anamika Chauhan


THE WAY WE COMMUNICATE, LEARN, AND WORK IS CHANGING AS A RESULT OF TECHNOLOGY.The world’s dependency on the Internet is growing all the time.Data is the most valuable resource on the planet. Protect   the information from prying eyes. When an organisation splits up, data is taken with it. To carry out such a future, we require high-security. As a result, IoT security has risen to the top of the priority list. In terms of privacy, authentication, and recovery from attacks.We have assembled a high level Network Intrusion Detection System (NIDS) in light of profound learning technique, we have used classical AI strategy such as (decision tree and random forest) and also deep-learing model like Artificial Neural Network and Convolutional neural network .we are utilizing the NSL-KDD data for training our model.

Index Terms—IOT,Neural Network,Intrusion Detection Sys- tem,Machine learning, Convolutional neural network.

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