Key Generation in Wireless Sensor Networks Based on Frequency-selective Channels - Design, Implementation, and Analysis

Key management in wireless sensor networks faces several new challenges. The scale, resource limitations, and new threats such as node capture necessitate the use of an on-line key generation by the nodes themselves. However, the cost of such schemes is high since their secrecy is based on computational complexity. Recently, several research contributions justified that the wireless channel itself can be used to generate information-theoretic secure keys. By exchanging sampling messages during movement, a bit string can be derived that is only known to the involved entities. Yet, movement is not the only possibility to generate randomness. The channel response is also strongly dependent on the frequency of the transmitted signal. In our work, we introduce a protocol for key generation based on the frequency-selectivity of channel fading. The practical advantage of this approach is that we do not require node movement. Thus, the frequent case of a sensor network with static motes is supported. Furthermore, the error correction property of the protocol mitigates the effects of measurement errors and other temporal effects, giving rise to an agreement rate of over 97%. We show the applicability of our protocol by implementing it on MICAz motes, and evaluate its robustness and secrecy through experiments and analysis.Comment: Submitted to IEEE Transactions on Dependable and Secure Computin

A Fast T-decomposition Algorithm

T-decomposition was first proposed and implemented as an algorithm by Mark Titchener. It has applications in communication of code sets and in the fields of entropy and similarity measurement. The first implementation of a T-decomposition algorithm by Titchener was subsequently followed by a faster version named tcalc, developed in conjunction with Scott Wackrow. An improved T-decomposition algorithm was published in 2003 by the authors with the implementation tlist. This paper introduces a new algorithm that builds on our 2003 algorithm. Comparative experimental results are given to show that the new version has a significantly better time performance than previous algorithms