A Formula Adaptive Pixel Pair Matching Steganography Algorithm

Author:

Long Min12ORCID,Li Fenfang1

Affiliation:

1. College of Computer and Communication Engineering, Changsha University of Science and Technology, 410114, China

2. Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, Changsha University of Science and Technology, Changsha, Hunan Province 410114, China

Abstract

Pixel pair matching (PPM) is widely used in digital image steganography. As an important derivation, adaptive pixel pair matching method (APPM) offers low distortion and allows embedded digits in any notational system. However, APPM needs additional space to store, calculate, and query neighborhood set, which needs extra cost. To solve these problems, a formula adaptive pixel pair matching (FAPPM) method is proposed in this paper. The basic idea of FAPPM is to use the formula to get the stego image pixel pair without searching the neighborhood set for the given image pixel pair. This will allow users to embed secret message directly without storing and searching the look-up table. Experimental results and analysis show that the proposed method could embed secret data directly without searching the neighborhood sets by using a formula and it still maintains flexibility in the selection of notional system, high image quality, and strong anti-steganalysis ability.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Computer Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep Learning-Based Image Steganography for Visual Data Cybersecurity in Construction Management;Journal of Construction Engineering and Management;2024-10

2. Improved Search Pattern with Discrete Wavelet Transform for Video Steganography;Proceedings of International Conference on Emerging Technologies and Intelligent Systems;2021-12-03

3. High-Capacity Convolutional Video Steganography with Temporal Residual Modeling;Proceedings of the 2019 on International Conference on Multimedia Retrieval;2019-06-05

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