Efficient Parallel Feature Selection for Steganography Problems Guillén, Alberto Rojas Ruiz, Ignacio Inteligencia artificial Artificial intelligence The steganography problem consists of the identification of images hiding a secret message, which cannot be seen by visual inspection. This problem is nowadays becoming more and more important since the World Wide Web contains a large amount of images, which may be carrying a secret message. Therefore, the task is to design a classifier, which is able to separate the genuine images from the non-genuine ones. However, the main obstacle is that there is a large number of variables extracted from each image and the high dimensionality makes the feature selection mandatory in order to design an accurate classifier. This paper presents a new efficient parallel feature selection algorithm based on the Forward-Backward Selection algorithm. The results will show how the parallel implementation allows to obtain better subsets of features that allow the classifiers to be more accurate. 2022-11-11T09:10:44Z 2022-11-11T09:10:44Z 2009 conference output Published version: Guillén, A... [et al.] (2009). Efficient Parallel Feature Selection for Steganography Problems. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. [https://doi.org/10.1007/978-3-642-02478-8_153] https://hdl.handle.net/10481/77911 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional Springer