Mitigation of network security attacks in wireless multimedia sensors networks using intrusion detection system

Abstract

<p>In this work, research propose a deep transfer learning-based Lecun network P-Lenet technique to move the knowledge contained in source domain data to the target domain and integrate to produce an efficient intrusion detection system (IDS) that would enhance the detection accuracy for any wireless multimedia sensors networks (WMSN) ecosystems. To prevent attacks on the software defined network (SDN) platform in real time, the proposed method placed a strong emphasis on anomaly detection as the primary mechanism. The Lecun network (LeNet) was investigated in this work, and a new variant of the network called the Lenet was proposed. In addition, research make use of techniques like as feature normalization to increase the accuracy of the algorithm predictions and to optimize the training process in such a way that it consumes the least amount of time and resources. The performance of the proposed model that was recommended was superior to that of existing network intrusion detection system (NIDS) algorithms.</p>