Adaboost and SVM based cybercrime detection and prevention model

Abstract

This paper aims to propose cybercrime detection and prevention model by using Support Vector Machine (SVM) andAdaBoost algorithm in order to reduce data damaging due to running of malicious codes. The performance ofthis model will be evaluated on a Facebook dataset, which includes benign executable and malicious codes. The mainobjective of this paper is to find the effectiveness of different classifiers on the Facebook dataset for crime detection.Finally, we try to compare the classifier accuracy of SVM and AdaBoost by using Weka 3.7.4 software in order to choosethe best model to classify the Facebook dataset with high accuracy.