ABSTRACT
The goal of a network-based IDS is to identify malicious behavior that targets a network and its resources. Intrusion detection parameters are numerous and in many cases they present uncertain and imprecise causal relationships which can affect attack types. A Bayesian Network is known as graphical modeling tool used to model decision problems containing uncertainty. BN is used to build automatic intrusion detection system based on signature recognition. The research provides a framework for an adaptive intrusion detection system that uses Bayesian network (naïve bayes).This project is implemented using java standard edition and Netbeans IDE which is an integrated development environment for java applications, and the KDD cup 99 data set.
OLAWALE, S (2021). Framework For Adaptive Intrusion Detection System Using Naïve Bayes Recognition. Afribary. Retrieved from https://afribary.com/works/framework-for-adaptive-intrusion-detection-system-using-naive-bayes-recognition
OLAWALE, SENJIRIN "Framework For Adaptive Intrusion Detection System Using Naïve Bayes Recognition" Afribary. Afribary, 07 Apr. 2021, https://afribary.com/works/framework-for-adaptive-intrusion-detection-system-using-naive-bayes-recognition. Accessed 20 Apr. 2024.
OLAWALE, SENJIRIN . "Framework For Adaptive Intrusion Detection System Using Naïve Bayes Recognition". Afribary, Afribary, 07 Apr. 2021. Web. 20 Apr. 2024. < https://afribary.com/works/framework-for-adaptive-intrusion-detection-system-using-naive-bayes-recognition >.
OLAWALE, SENJIRIN . "Framework For Adaptive Intrusion Detection System Using Naïve Bayes Recognition" Afribary (2021). Accessed April 20, 2024. https://afribary.com/works/framework-for-adaptive-intrusion-detection-system-using-naive-bayes-recognition