An Efficient Deep Learningbased Intrusion Detection System for Internet of Things Networks with Hybrid Feature Reduction and Data Balancing Techniques
Hamdullah Karamollaoğlu,
İbrahim Alper Doğru,
İbrahim Yücedağ
Abstract:With the increasing use of Internet of Things (IoT) technologies, cyber-attacks on IoT devices are also increasing day by day. Detecting attacks on IoT networks before they cause any damage is crucial for ensuring the security of the devices on these networks. In this study, a novel Intrusion Detection System (IDS) was developed for IoT networks. The IoTID20 and BoT-IoT datasets were utilized during the training phase and performance testing of the proposed IDS. A hybrid method combining the Principal Componen… Show more
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