Cubic B–spline fuzzy transforms for an efficient and secure compression in wireless sensor networks.

Joining data compression and encryption is a way to keep secure data, as discussed by the current literature. While data compression responds to the great demand on data storage and transmission techniques, the encryption allows to handle some important parameters in a secure way. In wireless sensor networks the usual transform–based compression is the Discrete Wavelet Transform. In a previous paper we showed the good perfomance of the fuzzy transform (or F–trasform for short) based compression with respect to it. In this work, we propose a cubic B–spline F–transform in order to have a higher accuracy, even when data are not correlated, and a lower computational cost. Besides, in order to show the efficiency of the proposed approach, we compare it with the most recent lossless compression scheme in the field. We discuss these issues formally and numerically by using publicly available real–world data sets. The parameters required to decompress data are encrypted by means of a suitable existing encryption algorithm. We show that even if an illegal user had access to one of these parameters, our scheme would be still secure. [ABSTRACT FROM AUTHOR]