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With the advancement of technology, cables have left most of our lives and have been replaced by wireless devices and environments. Especially, the use of wireless local area networks (WLAN) has increased rapidly in recent years and is expected to increase further. The popularity and rapid development of wireless technology has made our daily life easier, but it also brought with it the security problem. The current state of WLAN technologies makes the network vulnerable to attacks ranging from passive listening to active intervention [1]. Therefore, there has been an increased interest in intrusion detection systems among researchers [2]. Intrusion detection systems (IDS) are being developed against these harmful attacks, but most techniques used in these systems cannot cope with dynamic and complex cyber-attacks [1, 6]. In addition, security standards for WLAN have still not been clearly established and for protection, IDSs of similar wireless networks such as wireless sensor, Ad-Hoc, etc. are acceptable, but cannot guarantee the best performance [3].

Due to the intense interest in WLAN, researches in the field of IDS have increased. However, the intensity and types of attacks increase at the same rate with the speed of these researches [5]. In this study, it is aimed to contribute to the solution of the mentioned problems and determine dynamically various types of attacks coming over the WLAN network with high accuracy. In addition to accurately identifying attacks, it is also important that it be fast. Therefore, the number of features to be used with feature selection has been reduced first. Then, signature based technique was used to quickly …