Open AccessFlow-Based Rules Generation for Intrusion Detection System using Machine Learning Approach
Author(s) -
Yasir Saleem,
Usama Anwar,
Muhammad Khawar Bashir,
Sheraz Naseer,
Nadia Tabassum
Publication year - 2020
Publication title -
lahore garrison university research journal of computer science and information technology
Language(s) - English
Resource type - Journals
eISSN - 2521-0122
pISSN - 2519-7991
DOI - 10.54692/lgurjcsit.2020.0403100
Subject(s) - computer science , firewall (physics) , intrusion detection system , exploit , machine learning , denial of service attack , artificial intelligence , classifier (uml) , stateful firewall , network security , anomaly based intrusion detection system , application firewall , rule based system , computer security , c4.5 algorithm , the internet , data mining , naive bayes classifier , entropy (arrow of time) , support vector machine , network packet , world wide web , physics , extremal black hole , quantum mechanics , charged black hole