ABSTRACT
Security across network has become a major concern during this Covid-19 scenario. Security threats happens due to variety of reasons like theft of analytical property, software attacks, identity theft, stealing of equipment or information, sabotage, and information extraction. The wrong use of protocols over network also causes security threat. Introduction of data mining techniques in network security field plays a major role with data extraction, data transformation and analysation of the huge amount of data. The various data mining algorithms provides an insight to analyse and predict the data and the threats over the computer networks. This paper focusses on the approaches to predict security threats over networks using various classification algorithms. The four-classification algorithm majorly focussed here is Naive Bayes Classifier, Decision Tree Classifier, K Nearest Neighbours and Logistic Regression. It compares the performance of the above-mentioned classification algorithms to detect the threats.
ABSTRACT
Personal Healthcare Assistance providing Bot (PHAB) is an artificially intelligent personal healthcare assistant. Due to the recent COVID19 pandemic, various social distancing norms have been imposed causing a hindrance in accessing healthcare facilities. This application aims to provide smart diagnosis while attempting to minimize COVID-19 transmission among patients and healthcare workers, by analyzing symptoms to diagnose, predict the medical conditions and generate helpful suggestions and precautions to be followed based on the inputs provided by the user. This medical care partner can serve to be exceptionally valuable during the pandemic and surprisingly post pandemic as it holds the possibility to help clients in need of supportive care without them having to anticipate their visit to healthcare facilities. As the application aims to perform accurate and comprehensive diagnosis, it also holds potential to serve as a pre-screening intermediatory device to be used by healthcare officials.