RFPS: A Robust Feature Points Detection of Audio Watermarking for Against Desynchronization Attacks in Cyber Security

Wenhuan Lu,Neal N Xiong,Jianguo Wei,Yuqing He,Ling Li

doi:10.1109/access.2020.2984283

Abstract

Digital watermarking is an effective covert communication technique in the military field, which can solve the problems in traditional encryption. In general, the Spread Spectrum (SS) algorithm can well satisfy the requirements of concealment and anti-interference in the covert communication process. However, it has a natural defect in resisting desynchronization attacks. In this paper, we propose a Robust Feature Points Scheme (RFPS) against desynchronization attacks by calculating the maximum response value of the second-order derivative of the original audio signal. The maximum response value will be used as a feature point and the audio segments centering at the detected feature points are extracted for both watermark embedding and extraction process. This study mainly focuses on cropping attacks and pitch invariant Time-Scale Modification (TSM) attacks. The experimental results show that under non-uniform cropping attacks, the proposed method can extract the watermark information without any bit error rate. Even in the case of the pitch-invariant TSM attacks, the proposed scheme has great improvement compared with the existing works.

Highlights

In the modern military war, military communication equipment has become the primary target of both sides of the war
EXPERIMENTAL SETTINGS we evaluate the performance of the proposed Robust Feature Points Scheme (RFPS) through simulations
WORK With the development of computer networks, data security has become an urgent problem in cyber security

Summary

INTRODUCTION

In the modern military war, military communication equipment has become the primary target of both sides of the war. For traditional SS-based audio algorithm, there are two problems: host signal interference and poor robustness to desynchronization attacks. Xiang et al proposed a novel SS-based on the audio watermarking method which can remove the host signal interference and maintain higher embedding capacity and better robustness [20]. Whereas, these methods all have the weakness of desynchronization attacks.

PRELIMINARIES

Findings

CONCLUSIONS AND FUTURE WORK