Rekik, SiwarSelouani, Sid-AhmedGuerchi, DrissHamam, Habib2020-01-302020-01-3020122012Rekik, S., Selouani, S.-A., Guerchi, D., & Hamam, H. (2012). An autoregressive time delay neural network for speech steganalysis. In 2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012 (pp. 54–58). https://doi.org/10.1109/ISSPA.2012.63106129781467303828http://dx.doi.org/10.1109/ISSPA.2012.6310612https://hdl.handle.net/20.500.12519/81This conference paper is not available at CUD collection. The version of scholarly record of this Conference Paper is published in 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA) (2012), available online at: https://ieeexplore.ieee.org/document/6310612.Hiding a secret message in speech signal, called steganography, is used to provide secure communication. The detection of hidden information in the transmitted message called steganalysis. The purpose of steganalysis is to identify the presence of embedded information, and does not actually attempt to extract or decode the hidden data. An automated method is required for detecting the existence of hidden message, since the huge amount of channeled information. However, the development and evaluation of steganalysis algorithms is a challenging task. In this paper we advocate a new steganalysis technique to classify a speech as having hidden information or not, using a powerful and sophisticated classifier called Autoregressive Time Delay Neural Network (AR-TDNN). The originality of this AR-TDNN is its quite ability to detect secret messages hidden with different steganographic algorithms, although the variation of detection rate depends on the particular hiding techniques and amount of hidden information. © 2012 IEEE.enPermission to reuse abstract has been secured from Institute of Electrical and Electronics Engineers Inc.Auto-regressiveAutomated methodsData hidingDetection ratesEmbedded informationHidden informationHidden messagesSecret messagesSecure communicationsSpeech signalsSteganalysisSteganographic algorithmsTime delay neural networksAlgorithmsComputer simulationInformation scienceNeural networksTime delaySteganographyConference PaperCopyright : 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.