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Issue title: Artificial Neural Networks
Guest editors: Stefanos Kollias, Andreas Stafylopatis and Wlodzislaw Duch
Article type: Research Article
Authors: Neumann, Dirk | Eckmiller, Rolf; * | Baruth, Oliver
Affiliations: Division of Neural Computation, Department of Computer Science, University of Bonn, Roemerstr. 164, 53117 Bonn, Germany. Tel.: +49 228 73 4422; Fax: +49 228 73 4425; E-mail: neumann@nero.uni-bonn.de, eckmiller@nero.uni-bonn.de, baruth@nero.uni-bonn.de
Correspondence: [*] Corresponding author. E-mail: eckmiller@nero.uni-bonn.de.
Abstract: We describe a novel secure communication system (SCS) via public networks. For the generation of a unique pair of encryption module (EM) and decryption module (DM), learning algorithms are applied in combination with biometric data of the future DM-user. Subsequently, EM can be attached to any computer to form a generally usable encryption unit (EU) while DM, if attached to another computer to form the matching decryption unit (DU), can only be activated by the specific pair-generating DM-user. EU transforms spatial data to temporal data by means of spatio-temporal (ST) filters. DU uses a combination of analytical- and learning algorithms for decryption.
DOI: 10.3233/ICA-2007-14405
Journal: Integrated Computer-Aided Engineering, vol. 14, no. 4, pp. 345-353, 2007
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