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Article . 2019
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Fast Fourier Transform-Based Steganalysis of Covert Communications over Streaming Media

Authors: Peng, Jinghui; Tang, Shanyu; Jia, Li;

Fast Fourier Transform-Based Steganalysis of Covert Communications over Streaming Media

Abstract

Steganalysis seeks to detect the presence of secret data embedded in cover objects, and there is an imminent demand to detect hidden messages in streaming media. This paper shows how a new steganalysis algorithm based on Fast Fourier Transform (FFT) can be used to detect the existence of secret data embedded in streaming media. The proposed algorithm uses machine parameter characteristics and a network sniffer to determine whether the Internet traffic contains streaming channels. The detected streaming data is then transferred from the time domain to the frequency domain through FFT. The distributions of power spectra in the frequency domain between original VoIP streams and stego VoIP streams are compared in turn using t-test, achieving the p-value of 7.5686E-176 which is below the threshold. Results indicate that the proposed FFT-based steganalysis algorithm is effective in detecting the secret data embedded in VoIP streaming media.

Keywords

Cyber-security, Information-security

17 references, page 1 of 2

[1] X. Niu, Y. Yang (2006). Study on the Frame of Information Steganography and Steganalysis. Acta Electonica Sinica, 34(12A), 2421-2424.

[2] J. Lubacz, W. Mazurczyk, and K. Szczypiorski (2010). Voice over IP. IEEE Spectrum, 40-45.

[3] C. Kraetzer, and J. Dittmann (Jan. 2007). Mel-Cepstrum based steganalysis for VoIPsteganography. Proc. IS&T/SPIE Symposium on Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents VIII, San Jose, USA, pp. 650-661.

[4] C. Kraetzer, and J. Dittmann (2007). Pros and cons of Mel-Cepstrum based audio steganalysis using SVM classification. Information Hiding, Springer Berlin Heidelberg, 359-377.

[5] Q. Liu, A. H. Sung, and M. Qiao (2009). Temporal derivative-based spectrum and mel-cepstrum audio steganalysis. IEEE Transactions on Information Forensics and Security, 4(3), 359-368.

[6] Q. Liu, A. H. Sung, and M. Qiao (2011). Derivative-based audio steganalysis. ACM Transactions on Multimedia Computing, Communications and Applications, 7(3), 1- 19.

[7] T. Takahashi T, and W. Lee (2007). An assessment of VoIP covert channel threats. Proc. 3rd Int Conf Security and Privacy in Communication Networks, Nice, France, 371-380.

[8] G. Garateguy, G. Arce, and J. Pelaez (2011). Covert channel detection in VoIP streams. Proc. 45th Annual Conference on Information Sciences and Systems, Baltimore, Maryland, 1-6.

[9] C. Arackaparambil, G. Yan, S. Bratus, and A. Caglayan (2012). On tuning the knobs of distribution-based methods for detecting VoIP covert channels. Proc. Hawaii International Conference on System Sciences, Hawaii, 2431-2440. [OpenAIRE]

[10] S. Li, H. Tao, and Y. Huang (2012). Detection of quantization index modulation steganography in G. 723.1 bit stream based on quantization index sequence analysis. Journal of Zhejiang University Science C, 13(8), 624-634.

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