Flow-Based Rules Generation for Intrusion Detection System using Machine Learning Approach | Zendy

Yasir Saleem | Zendy; Usama Anwar | Zendy; Muhammad Khawar Bashir | Zendy; Sheraz Naseer | Zendy; Nadia Tabassum | Zendy

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Flow-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

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