A Survey of Methods for the Construction of an Intrusion Detection System

TitreA Survey of Methods for the Construction of an Intrusion Detection System
Type de publicationCommunications avec actes
Année de publication2020
Titre de la Conférence/colloqueInternational Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2019)
Titre des actes ou de la revueArtificial Intelligence and Applied Mathematics in Engineering Problems
Pagination211 - 225
jour/mois du congrès, colloque20-22/04/2019
Auteur(s)Kassem, A. Karim, Arkoub S. Abo, Daya B. et Chauvet P.
Directeur(s)D. Hemanth, J. et Kose U.
Université, EditeurSpringer International Publishing
Ville, PaysAntalya, Turquie
Numéro ISBN978-3-030-36178-5

Cybercrimes committed using computer networks lead to billions of dollars lose, the illegal access into computer system, stealing valuable data and destroying organization networks which in turn affect the cyber resources. Because of the expansion of attacks or threats on the networks infrastructure, which is nothing but can be consider as an illegitimate intrusion, based on the machine learning methodology, the intrusion detection system (IDS) can consider as one of the most used cyber security mechanisms, thus to detect the promiscuous activities against sensitive and private data. In this paper our target is to provide a guide lines for researchers and developers discussing the IDS construction phases and their latest techniques, we will clarify the most applied data sources employed in the proposition of a model that will be built for the purpose of creating an intelligent detection system. Furthermore, this survey presents the most commons and latest methods employed and used for designing an IDS based on the data mining techniques and discusses the artifacts removal by summarizing the advantages with the disadvantages of the currents methods and addressing the last novel steps into this field of research.