An Intrusion Detection Using Machine Learning Algorithm Multi-Layer Perceptron (MlP): A Classification Enhancement in Wireless Sensor Network (WSN)

During several decades, there has been a meteoric rise in the development and use of cutting-edge technology. The Wireless Sensor Network (WSN) is a groundbreaking innovation that relies on a vast network of individual sensor nodes. The sensor nodes in the network are responsible for collecting data and uploading it to the cloud. When networks with little resources are deployed harshly and without regulation, security risks occur. Since the rate at which new information is being generated is increasing at an exponential rate, WSN communication has become the most challenging and complex aspect of the field. Therefore, WSNs are insecure because of this. With so much riding on WSN applications, accuracy in replies is paramount. Technology that can swiftly and continually analyse internet data streams is essential for spotting breaches and assaults. Without categorization, it is hard to simultaneously reduce processing time while maintaining a high level of detection accuracy. This paper proposed using a Multi-Layer Perceptron (MLP) to enhance the classification accuracy of a system. The proposed method utilises a feed-forward ANN model to generate a mapping for the training and testing datasets using backpropagation. Experiments are performed to determine how well the proposed MLP works. Then, the results are compared to those obtained by using the Hoeffding adaptive tree method and the Restricted Boltzmann Machine-based Clustered-Introduction Detection System. The proposed MLP achieves 98% accuracy, which is higher than the 96.33% achieved by the RBMC-IDS and the 97% accuracy achieved by the Hoeffding adaptive tree

BSDD: Biomolecules Segment Display Device—a web-based interactive display tool

An interactive web-based display tool, Biomolecules Segment Display Device (BSDD), has been developed to search for and visualize a user-defined motif or fragment among the protein structures available in the Protein Data Bank (PDB). In addition, the tool works for the structures available in a selected sub-set of non-homologous protein structures (25% and 90% sequence identity). The graphics package RASMOL has been incorporated as an interface to visualize the three-dimensional structure of the user-defined motif. In addition, the software can be used to extract the atomic coordinates of the required fragment and save them to the client system. The atomic coordinates are updated every week from the RCSB–PDB server, and hence the results produced by BSDD are up to date at any given time. The software BSDD is available over the World Wide Web at http://iris.physics.iisc.ernet.in/bsdd or http://144.16.71.2/bsdd