Reputation management using honeypots for intrusion detection in the internet of things

Abstract

Internet of Things (IoT) networks consist of tiny devices with limited processing resources and restricted energy budget. These devices are connected to the world-wide web (www) using networking protocols. Considering their resource limitations, they are vulnerable to security attacks by numerous entities on the Internet. The classical security solutions cannot be directly implemented on top of these devices for this reason. However, an Intrusion Detection System (IDS) is a classical way to protect these devices by using low-cost solutions. IDS monitors the network by introducing various metrics, and potential intruders are identified, which are quarantined by the firewall. One such metric is reputation management, which monitors the behavior of the IoT networks. However, this technique may still result in detection error that can be optimized by combining this solution with honeypots. Therefore, our aim is to add some honeypots in the network by distributing them homogeneously as well as randomly. These honeypots will team up with possible maliciously behaving nodes and will monitor their behavior. As per the simulation results, this technique reduces the error rate within the existing IDS for the IoT; however, it costs some extra energy. This trade-off between energy consumption and detection accuracy is studied by considering standard routing and MAC protocol for the IoT network.