A prediction model for cybercrime in social media using data mining techniques

Abstract

The world has developed to trust on internet communications everywhere the newlinereal time dataset and information are composed .Small and huge data set and also its newlineinformation in various domains like as medical, retails, social media, products newline,businesses, customers, resources and suppliers. Prediction is done by checking out newlinethe knowledge of some pattern from large amount of data. Classification is one of newlinethe most frequently analyzed problems done by data mining and machine learning newline(ML). newlineThe main objective of the CCP Model is to build new cybercrime predictive newlinemodel to envisage future social medial crimes and find the efficiency of different newlineclassifiers on the social media dataset for crime detection and also to classifier newlineaccuracy of SVM, c4.5, KNN and Naive Bayes using open source data mining tool newlinein order to choose the best model to classify the social media dataset with high newlineaccuracy rate. Classification consists of forecasting a certain result based on a given newlineinput and it is a method to classify our data. This CCP help to stop the crime prior to newlinestart and this model helps to predict the future crime incidence areas or forecasting newlinecrimes in social media newlineThe extended work of this research project is to develop provide unified newlineexperience to the analyser via web and mobile to do CCP analyze, To provide API newlineview to partner for checking and getting CCP model data for prediction, Police will newlinebe able to setup the preference area to find the analyse based on set of category and newlineProvide notification to police via mail or SMS if any future crime is predicted newline