DETECTING DOS ATTACKS IN THE INTERNET OF THINGS (IOT) USING INTELLIGENT NEURAL NETWORK

Farzane Mohamady, Pouya Asadi, Akbar Morshed Aski

Abstract


ICT is increasingly used in the last decade. One of the greatest challenges in this area is the system and information security. This security is threatened by cyberattacks on networks. New techniques have been devised for the field by expanding research into network security. Among the most popular techniques, various data mining algorithms can be noted that are used either alone or in combination with intrusion detection. In this study, a neural network technique was used for intrusion detection. The results of the simulation of this technique on the KDD dataset and MATLAB software indicated a high precision of 98%. A comparison of this technique with other techniques such as CNN and BiLSTM suggested that these techniques had less precision than the proposed one. In addition, the technique had a low error rate.

Keywords


intrusion detection, cyberattacks, neural networks, data mining.

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References


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