Adaboost and SVM based cybercrime detection and prevention model

hanif - Mohaddes Deylami, Yashwant Prasad Singh

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.


Full Text: PDF DOI: 10.5430/air.v1n2p117

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

Artificial Intelligence Research

ISSN 1927-6974 (Print)   ISSN 1927-6982 (Online)

Copyright © Sciedu Press 
To make sure that you can receive messages from us, please add the 'Sciedu.ca' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.