Naive Bayes Untuk Mendeteksi Gangguan Jaringan Komputer Dengan Seleksi Atribut Berbasis Korelasi

Abstract

Internet increasing is also exponentially increasing intrusion or attacks by crackers exploit vulnerabilities in Internet protocols , operating systems and software applications . Intrusion or attacks against computer networks , especially the Internet has increased from year to year . Intrusion detection systems into the main stream in the information security . The main purpose of intrusion detection system is a computer system to help deal with the attack . This study presents a correlation-based feature selection to detect computer network intrusions . Feature selection result applied on naive bayes algorithm. Performance is measured based on the level of accuracy , sensitivity , precision and spesificity . Dataset used in this study is a dataset KDD 99 intrusion detection system . Dataset is composed of two training data and testing data . From the experimental results obtained by the accuracy of naive Bayes without feature selection 76,12 %, and the accuracy with feature selection 81,89 %. Correlaiton-based feature selection can improve naive bayes accuration. Keyword: naive bayes, intrusion detection, correlation-based fetaure selection