IoT Intrusion Detection Model Using RNN Algorithm

An Intrusion Detection System (IDS) is the method that is processed in the network layer of an IoT system. Machine learning techniques have been applied in the IDS and observed the higher performance in identifying the intrusion and malware. The existing method involved in IDS tends to be ineffective due to the drawbacks of big data, centralization, and low privacy. The existing method is also inefficient in handling the streaming data of IoT systems. Most of the method in the IDS has low efficiency in intrusion detection to increase the efficiency of the detection. In this research, the FPA is proposed in IoT intrusion detection to increase the efficiency of the detection.