Fast Fourier Transform-based steganalysis of covert communications over streaming media

Peng, Jinghui, Tang, Shanyu ORCID: https://orcid.org/0000-0002-2447-8135 and Jia, Li (2019) Fast Fourier Transform-based steganalysis of covert communications over streaming media. International Journal of Computer and Information Engineering, 13 (7). pp. 362-367. ISSN 2010-376X

[img]
Preview
PDF
Shanyu_Jia_and_Peng_IJICCS_2019_Fast_Fourier_Transform-based_steganalysis_of_covert_communications_over_streaming_media.pdf - Accepted Version
Available under License Creative Commons Attribution Share Alike.

Download (381kB) | Preview

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.

Item Type: Article
Additional Information: This work was supported in part by various industrial sponsors under Grant 28801.
Uncontrolled Keywords: Steganalysis, Security, Fast Fourier Transform (FFT), Streaming media
Subjects: Computing > Information security > Cyber security
Computing > Information security
Related URLs:
Depositing User: Shanyu Tang
Date Deposited: 17 Sep 2019 15:48
Last Modified: 04 Oct 2019 13:46
URI: http://repository.uwl.ac.uk/id/eprint/6383

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item

Menu