Use of Smart Intrusion Detection System for Enhancing the Security in Hierarchical Wireless Sensor Network (International Journal of Innovative Research in Computer Science & Technology, 2021)
Trusted environment provides safety  measures for the sensor network. There are many  problems that occur during the management of resources.  Memory management and computation overhead or CPU  usage are the major issues. Security issues is another  problem in Wireless sensor network.. The three types of  issues like issues of memory, computation overhead and  intrusion detection is considered in this proposed research.  The proposed model has provided a mechanism for  resource management in a wireless sensor network. This  model would also resolve one diff type of issue like  computation overhead. The proposed work is capable to  classify IDS attacks using a deep learning model. For  improving accuracy a Network model is proposed during  intrusion detection using a recurring neural network. The  network model is used for testing by the help of a  confusion matrix to calculate The accuracy, precision,  recall and fscore. For clustered wireless sensor networks  the advanced adaptive and dual data communication trust  scheme (adct) have been used. Research is able to handle  untrustworthy nodes inefficient manner. A function that is  used in this research to assess direct trust among nodes is  called Adaptive trust function. In intracluster as well as  intercluster this Trust mechanism ADCT is used. With the  help of compression mechanism Packets have been  compressed for reducing the computation overhead. For  security in Intrusion, this proposed model would also be  capable. Moreover, research work would also deal with  selfish nodes and malicious nodes to provide better of  service for network lifetime for different network sizes.
Keywords: Wireless Sensor Network; IDS; intrusion detection system; Trust management; LSTM