ID-ELC: Intrusion Detection by Ensemble Learning and Classification for Internet of Things (IoT)

Ravinder Korani and Dr.P. Chandra Sekhar Reddy

The remarkable and constant increase of divergent IoT dependent networks is open for connectivity & security challenges. Here, this is because of IoT devices nature, internetworking loosely coupled conduct, & networks heterogenic structure. These parameters are vulnerable highly towards flow of traffic. The botnets such as “mirai” noticed in recent past exploits the devices of IoT and change them for traffic overflow such that required network deplete towards the response of benign requests. Therefore, the research of this paper suggested a new learning-based method, which learns from features of traffic flow determined for distinguishing the benign traffic flows and botnet-initiated traffic. The analysis of performance is conducted experimentally by utilizing the combined traffic flows, which are huge in quantity and attacks source. Values achieved for the statistical metrics were showing robustness and importance of the suggested method.

Volume 11 | Issue 6

Pages: 161-173