An Accurate Detection Approach for IoT Botnet Attacks Using Interpolation Reasoning Method

Nowadays, the rapid growth of technology delivers many new concepts and notations that aim to increase efficiency comfort human life. One these techniques is Internet Things (IoT). The IoT has been used achieve efficient operation management, cost-effective operations, better business opportunities, etc. However, there are challenges facing implementing an smart environment. most critical challenge protecting environment from different attacks. Botnet attacks considered a serious challenge. danger this attack lies in it could be for several threatening commands. Therefore, implemented perform DDoS attacks, phishing spamming, other scenarios. This paper introduced detection approach against using interpolation reasoning method. suggested was method instead classical methods handle knowledge base issues reduce size fuzzy rules. designed, tested, evaluated open-source benchmark dataset. experiments show able detect effectively with 96.4% rate. Furthermore, obtained results were compared literature results; accomplished comparison showed rivalry methods, reduced false positive rate interpolated alerts even case sparse rule base.