Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography

Peng, J, Jiang, Y, Tang, S and Meziane, F ORCID: 2021, 'Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography' , IEEE Transactions on Dependable and Secure Computing, 18 (4) , pp. 1962-1973.

PDF - Accepted Version
Download (7MB) | Preview
Access Information: © 2019 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.


Voice over IP (VoIP) is finding its way into several applications, but its security concerns still remain. This paper shows how a new self-adaptive steganographic method can ensure the security of covert VoIP communications over the Internet. In this study an Active Voice Period Detection algorithm is devised for PCM codec to detect whether a VoIP packet carries active or inactive voice data, and the data embedding location in a VoIP stream is chosen randomly according to random sequences generated from a logistic chaotic map. The initial parameters of the chaotic map and the selection of where to embed the message are negotiated between the communicating parties. Steganography experiments on active and inactive voice periods were carried out using a VoIP communications system. Performance evaluation and security analysis indicates that the proposed VoIP steganographic scheme can withstand statistical detection, and achieve secure real-time covert communications with high speech quality and negligible signal distortion.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: IEEE Transactions on Dependable and Secure Computing
Publisher: IEEE
ISSN: 1545-5971
Related URLs:
Funders: National Natural Science Foundation of China
Depositing User: Prof Farid Meziane
Date Deposited: 10 Oct 2019 12:29
Last Modified: 16 Feb 2022 02:54

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)


Downloads per month over past year