New scheme to prevent node replication attacks for wireless sensor networks

Abstract

Wireless sensor networks are a relatively new technology for information gathering and processing. A sensor network usually consists of many, resource constrained sensor nodes. These nodes perform measurements of some physical phenomena, process data, generate reports, and send these reports via multihop communication to a central information processing unit called sink. Depending on the scenario, information gathering and processing is collaboratively performed by multiple sensor nodes, e.g., to determine the average temperature in a certain area. Sensor networks can be used in a plethora of application scenarios. Emerging from military research, e.g., sensor networks for target tracking in a battle field, sensor networks are nowadays used more and more in civil applications such as critical infrastructure monitoring. For ensuring the functionality of a sensor network, especially in malicious environments, security mechanisms are essential for all sensor networks. However, sensor networks differ from classical (wireless) networks and this consequently makes it harder to secure them. Reasons for this are resource constraints of the sensor nodes, the wireless multihop communication, and the possibility of node compromise. Since sensor nodes are often deployed in unattended or even hostile environments and are usually not equipped with tamper-resistant hardware, it is relatively easy to compromise a sensor node. So, the sensor network can suffer from various types of attacks and threats. Among them, a mentionable attack is node clone. In node clone attacks, an attacker seizure a node and gets all the credential like ID, cryptographic key, code, data, etc., of that node. With this information the adversary made more replica node in the network. Various schemes have been offered for identification of node clone attacks. But they have some limitations. This work proposes a centralized system for clone identification. We split the network into segments and select an inspection node for each segment. Inspection node identifies a clone node by checking the node’s ID and cryptographic key. We also proposed honeypot technique which increases the replica detection performance. Finally, we provide solution for two cases of blacklisted replica nodes: The cases are when the cluster head compromised and the when the normal node is compromised. Experimental shows that the solutions improve the network performance.