Rule-Based Anomaly Detection Technique Using Roaming Honeypots for Wireless Sensor Networks

Abstract

Because the nodes in a wireless sensor network (WSN) are mobile and the network is highly dynamic, monitoring every node at all times is impractical. As a result, an intruder can attack the network easily, thus impairing the system. Hence, detecting anomalies in the network is very essential for handling efficient and safe communication. To overcome these issues, in this paper, we propose a rule‐based anomaly detection technique using roaming honeypots. Initially, the honeypots are deployed in such a way that all nodes in the network are covered by at least one honeypot. Honeypots check every new connection by letting the centralized administrator collect the information regarding the new connection by slowing down the communication with the new node. Certain pre‐defined rules are applied on the new node to make a decision regarding the anomality of the node. When the timer value of each honeypot expires, other sensor nodes are appointed as honeypots. Owing to this honeypot rotation, the intruder will not be able to track a honeypot to impair the network. Simulation results show that this technique can efficiently handle the anomaly detection in a WSN.

Strategic Honeypot Deployment in Ultra-Dense Beyond 5G Networks: A Reinforcement Learning Approach

“…In more detail, the main goal of WHs is to gather information about the attacks performed on wireless networks and the associated technologies, focusing on the attacks that exploit the wireless technologies' weaknesses, which are mainly due to the use of unguided transmission medium [17]. The main principles of the WHs can be used in several types of networks, including cellular, Local Area Networks (LANs), sensor networks and Unmanned Aerial Vehicles (UAVs)-based networks [18].…”