Abstract: In this work we investigate the possibility to use the measurement matrices from compressed sensing as secret key to encrypt / decrypt signals. Practical results and a comparison between BP (basis pursuit) and OMP (orthogonal matching pursuit) decryption algorithms are presented. To test our method, we used 10 text messages (10 different tax forms) and we generated 10 random matrices and for distortion validate we used the PRD (the percentage root-mean-square difference), its normalized version (PRDN) measures and NMSE (normalized mean square error). From the practical results we found that the time for BP algorithm is much higher than for OMP algorithm and the errors are smaller and should be noted that the OMP does not guarantee the convergence of the algorithm. We found that it is more advantageous, for tax forms (or other templates that show no interest for encryption) to encrypt only the recorded data. The time required for decoding is significantly lower than the decryption for the entire form

Adrian Brezulianu, Monica Fira and Marius Daniel Pestina, “Compressed Sensing Based Encryption Approach for Tax Forms Data” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 4(11), 2015. http://dx.doi.org/10.14569/IJARAI.2015.041106

@article{Brezulianu2015,
title = {Compressed Sensing Based Encryption Approach for Tax Forms Data},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2015.041106},
url = {http://dx.doi.org/10.14569/IJARAI.2015.041106},
year = {2015},
publisher = {The Science and Information Organization},
volume = {4},
number = {11},
author = {Adrian Brezulianu and Monica Fira and Marius Daniel Pestina}
}