In situ key establishment in large-scale sensor networks

  • Authors:
  • Yingchang Xiang;Fang Liu;Xiuzhen Cheng;Dechang Chen;David H. C. Du

  • Affiliations:
  • Department of Basic Courses, Rizhao Polytechnic College, Rizhao, Shandong, China;Department of Computer Science, University of Texas -Pan American, Edinburg, Texas;Department of Computer Science, The George Washington University, Washington, DC;Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, Bethesda, MD;Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking - Special issue on wireless network security
  • Year:
  • 2009

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Abstract

Due to its efficiency, symmetric key cryptography is very attractive in sensor networks. A number of key predistribution schemes have been proposed, but the scalability is often constrained by the unavailability of topology information before deployment and the limited storage budget within sensors. To overcome this problem, three in-situ key establishment schemes, SBK, LKE, and iPAK, have been proposed. These schemes require no preloaded keying information but let sensors compute pairwise keys after deployment. In this paper, we propose an in-situ key establishment framework of which iPAK, SBK, and LKE represent different instantiations. We further compare the performance of these schemes in terms of scalability, connectivity, storage, and resilience. Our simulation results indicate that all the three schemes scale well to large sensor networks. We also notice that SBK outperforms LKE and LKE outperforms iPAK with respect to topology adaptability. Finally, observing that iPAK, SBK, and LKE all rely on the key space models that involve computationally intensive modular operations, we propose an improvement that rely on random keys that can be easily computed from a secure pseudorandom function. This new approach requires no computation overhead at regular worker sensors, therefore has a high potential to conserve the network resource.