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Öğe Gri Kurt Algoritması ile Saldırı Tespit Sistemleri İçin Yeni Bir Yaklaşım(Selçuk Üniversitesi Fen Bilimleri Ensititüsü, 2022) Al-Khazraji, Samra Suhdee; Kahramanlı Örnek, HumarCyber-attacks and the size of network data are increasing dramatically, and new methods have been developed to keep organizations and data networks safe from developing dynamic threat types. When more security tools and sensors are used in the existing corporate network, the amount of security event and alert data that is generated continues to increase, making system flow difficult. Institutions should rely on new technologies to assist and increase the number of human analysts in dealing with, preventing, detecting, responding to, and responding to cyber safety incidents and potential attacks on their networks. In recent years, as organizations have moved towards computer dependence and automation, it is essential to create secure applications, systems, and networks. In addition to these difficulties, the number of threats increases significantly due to the increase in the attack surface thanks to the multiple interfaces available for each service. To mitigate the impact of these threats, researchers have suggested several solutions; however, existing tools often fail to adapt to ever-changing structures and related threats. Artificial neural networks based on the gray wolf optimization algorithm has designed for intrusion detection systems for types of intrusion detection systems (IDS), their capabilities and methods of use in design.