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2021-02-08
Nisperos, Z. A., Gerardo, B., Hernandez, A..  2020.  Key Generation for Zero Steganography Using DNA Sequences. 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). :1–6.
Some of the key challenges in steganography are imperceptibility and resistance to detection of steganalysis algorithms. Zero steganography is an approach to data hiding such that the cover image is not modified. This paper focuses on the generation of stego-key, which is an essential component of this steganographic approach. This approach utilizes DNA sequences and shifting and flipping operations in its binary code representation. Experimental results show that the key generation algorithm has a low cracking probability. The algorithm satisfies the avalanche criterion.
2015-05-04
Zurek, E.E., Gamarra, A.M.R., Escorcia, G.J.R., Gutierrez, C., Bayona, H., Perez, R., Garcia, X..  2014.  Spectral analysis techniques for acoustic fingerprints recognition. Image, Signal Processing and Artificial Vision (STSIVA), 2014 XIX Symposium on. :1-5.

This article presents results of the recognition process of acoustic fingerprints from a noise source using spectral characteristics of the signal. Principal Components Analysis (PCA) is applied to reduce the dimensionality of extracted features and then a classifier is implemented using the method of the k-nearest neighbors (KNN) to identify the pattern of the audio signal. This classifier is compared with an Artificial Neural Network (ANN) implementation. It is necessary to implement a filtering system to the acquired signals for 60Hz noise reduction generated by imperfections in the acquisition system. The methods described in this paper were used for vessel recognition.