A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method.

Balyan, Amit Kumar; Ahuja, Sachin; Lilhore, Umesh Kumar; Sharma, Sanjeev Kumar; Manoharan, Poongodi; Algarni, Abeer D; Elmannai, Hela; Raahemifar, Kaamran

Balyan, Amit Kumar; Ahuja, Sachin; Lilhore, Umesh Kumar; Sharma, Sanjeev Kumar; Manoharan, Poongodi; Algarni, Abeer D; Elmannai, Hela; Raahemifar, Kaamran.

Afiliación

Balyan AK; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Ahuja S; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Lilhore UK; KIET Group of Institutions, Delhi-NCR, Ghaziabad 201206, India.
Sharma SK; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Manoharan P; Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha 500001, Qatar.
Algarni AD; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Elmannai H; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Raahemifar K; College of Information Sciences and Technology, Data Science and Artificial Intelligence Program, Penn State University, State College, PA 16801, USA.

Sensors (Basel) ; 22(16)2022 Aug 10.

Article en En | MEDLINE | ID: mdl-36015744

Asunto(s)

Algoritmos; Máquina de Vectores de Soporte; Aprendizaje Automático

Palabras clave

Hybrid IDS; genetic algorithm; intrusion detection; machine learning; particle swarm optimization; random forest; security

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Máquina de Vectores de Soporte Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: India Pais de publicación: Suiza

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