Abstract
Steganalysis deals with detecting the presence of hidden information in different types of media such as images and audio files. Such detection is very challenging because of the variety of algorithms that might be used in embedding secret information in a media type. This chapter presents a reliable Steganalyzer system with distributed services oriented architecture which allows easy incorporation of new algorithms to support different media types in the existing system. Moreover, the distributed architecture presented in this chapter allows concurrent processing which speeds up the system. High system reliability in distinguishing between the cover object and the stego object is achieved by employing multiple steganalysis algorithms, and further by employing efficient feature classifiers based on neural networks. The system developed is versatile with capabilities of detecting stego objects in JPEG images as well as WAV audio files.
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References
http://www.javaworld.com/javaworld/jw-06–2005/jw-0613-soa.html
Liu Q, Sung AH, Qiao M (2009) Novel stream mining for audio steganalysis. In: Proceedings of the seventeen ACM international conference on Multimedia, Beijing, China, 19 –24 Oct 2009, pp 95–104
Gonzalez R, Woods R (2008) Digital image processing, 3rd edn. Prentice Hall, New Jersey
Kraetzer C , Dittmann J (2007) Mel-cepstrum based Steganalysis for VOIP-steganography. In: Proceedings of the SPIE, vol 6505, San Jose, CA, USA
Ellis D, PLP and RASTA (and MFCC, and inversion) in Matlab using melfcc.m and invmelfcc.m. Available at http://labrosa.ee.columbia.edu/matlab/rastamat/
Liu Q, Sung AH, Qiao M (2009) Improved detection and evaluation for JPEG Steganalysis. In: Proceedings of the seventeen ACM international conference on Multimedia, Beijing, China, Oct 19 –24 2009, pp 873–876
Zilouchian A, Jamshidi M (eds) (2001) Fundamentals of neural networks. Intelligent control systems using soft computing methodologies. CRC Press, Boca Raton
Hetzl S, Mutzel P (2005) A graph-theoretic approach to steganography, vol 3677, LNCS, pp 119–128. The code is available at http://steghide.sourceforge.net/
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Abdelfattah, E., Mahmood, A. (2013). A Multi-Algorithm, High Reliability Steganalyzer Based on Services Oriented Architecture. In: Sobh, T., Elleithy, K. (eds) Emerging Trends in Computing, Informatics, Systems Sciences, and Engineering. Lecture Notes in Electrical Engineering, vol 151. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3558-7_45
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DOI: https://doi.org/10.1007/978-1-4614-3558-7_45
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