Many key pre-distribution techniques have been developed recently to establish pairwise keys between sensor nodes in wireless sensor networks. To further improve these schemes, researchers have also proposed to take advantage of the sensors' expected locations and discovered locations to help the pre-distribution of the keying materials. However, in many cases, it is very difficult to deploy sensor nodes at their expected locations or guarantee the correct location discovery at sensor nodes in hostile environments. In this chapter, a group-based deployment model is developed to improve key pre-distribution. In this model, sensor nodes are only required to be deployed in groups. The critical observation in the chapter is that the sensor nodes in the same group are usually close to each other after deployment. This deployment model is practical; it greatly simplifies the deployment of sensor nodes, while still providing an opportunity to improve key pre-distribution. Specifically, the chapter presents a novel framework for improving key pre-distribution using the group-based deployment knowledge. This framework does not require the knowledge of the sensors' expected or discovered locations and is thus suitable for applications where it is difficult to deploy the sensor nodes at their expected locations or correctly estimate the sensors' locations after deployment. To seek practical key pre-distribution schemes, the chapter presents two efficient instantiations of this framework, a hash key-based scheme and a polynomial-based scheme. The evaluation shows that these two schemes are efficient and effective for pairwise key establishment in sensor networks; they can achieve much better performance than the previous key pre-distribution schemes when the sensor nodes are deployed in groups.
|Original language||English (US)|
|Title of host publication||Security In Ad-hoc And Sensor Networks|
|Publisher||World Scientific Publishing Co. Pte Ltd|
|Number of pages||36|
|State||Published - Sep 18 2009|
ASJC Scopus subject areas
- Computer Science(all)