2012 Tenth Annual International Conference on Privacy, Security and Trust 978-1-4673-2326-0/12/$31.00 ©2012 IEEE 195 CENTER: A Centralized Trust-Based Efficient Routing Protocol for Wireless Sensor Networks Ayman Tajeddine Ayman Kayssi Ali Chehab Department of Electrical and Computer Engineering American University of Beirut Beirut 1107 2020, Lebanon {ast03, ayman, chehab}@aub.edu.lb Abstract — In this paper, we present CENTER, a CENtralized Trust-based Efficient Routing protocol for wireless sensor networks (WSN). CENTER is a secure and efficient routing protocol that utilizes the powerful sink base station (BS) to identify and ban different types of misbehaving nodes that may interrupt or abuse the functionality of the WSN. In CENTER, the BS periodically accumulates simple local observations of every node and deduces a detailed global view of the network. The BS calculates different quality metrics – namely the maliciousness, cooperation, and compatibility, approximates the battery life, and evaluates the Data Trust and Forwarding Trust values of each node. The BS then uses an effective technique to isolate all “bad” nodes, whether misbehaving or malicious, based on their history. Finally, the BS uses an efficient method to disseminate updated routing information, indicating the uplinks and the next hop downlink for every node. Through its centralized approach, CENTER provides more efficient and secure routing while accounting for the energy-constrained sensor nodes. We present simulation results of CENTER performed using TOSSIM to verify its correctness, security, and reliability. Keywords-component; Wireless Sensor Networks; Trust; Centralized Routing Protocol, misbehaving nodes. I. INTRODUCTION Wireless sensor network (WSN) technology has gained much attention in the past few years as it promises to improve data collection and statistical analysis [1]. However, with the severely-constrained sensor nodes, several security and energy concerns arise [2]. There are several methods to detect misbehaving nodes and provide secure routing, a critical issue in WSNs, while accounting for energy consumption and lengthening the network lifetime, another critical issue in WSNs. Among these are: reputation-based and trust-based methods [3], location isolation [4], and behavior-based techniques [5]. Reputation-based trust methods are essential to maintain secure routing and isolate misbehaving nodes; however these methods require energy-consuming inquiries from every node to its one-hop neighbors (and sometimes two-hops or farther neighbors). In addition, these methods incur additional processing overhead at sensor nodes to calculate the trust values of every neighbor. With the severely-constrained sensor nodes, it is essential to decrease the load on them to a minimum. It is therefore preferred to delegate these calculations and inquiries to a more powerful network entity. Most WSNs contain a sink node that is connected to AC power and usually possesses much higher processing and energy capabilities than the sensor nodes. The main function of this sink node is to gather the readings from the different sensors and make use of them in the way that the WSN was intended for. As a result, and with the knowledge that in a WSN all nodes have the same trust criteria – trust in correct routing of packets, we utilize in this paper the centralized approach and delegate the trust and reputation inquiries and calculations and the routing computations to this sink BS. An inherent benefit that is gained from this approach is that the BS has a global view of the network, which yields more trusted and correct routing information. We therefore present CENTER, based on our two previous schemes in [6] and [7], as a CENtralized Trust-based Efficient Routing protocol for WSNs. Utilizing the centralized approach, CENTER uses the more powerful and more knowledgeable BS to provide a more trusted network environment with more efficient and secure routing paths, while decreasing the load on the severely-constrained sensor nodes. In CENTER, the sink BS periodically gathers observations from the individual nodes about the number of packets sent through neighbors and then, it performs several checks and calculations to have a better and more accurate view of the network. Furthermore, the BS approximates the battery life of every node based on its presumed activity and calculates several quality metrics for every node, namely the maliciousness, cooperation, and competence levels. Then, the BS evaluates two trust values for each node – namely Data Trust and Forwarding Trust. Following the quality metrics calculations, the BS is able to detect several types of “bad” nodes: a malicious node sending false or illogical information, a non-cooperative node not reliably forwarding the packets of other nodes, or a malfunctioning/malicious node broadcasting packets. The bad nodes are isolated for a period of time that depends on their history. In addition to bad nodes, the BS can detect incompetent nodes that are unable to correctly deliver packets to it due to different non-malicious reasons. The BS will avoid