A combination of least significant bit and deflate compression for image steganography

Author:

Tayyeh Huda Kadhim,Ahmed AL-Jumaili Ahmed Sabah

Abstract

Steganography is one of the cryptography techniques where secret information can be hidden through multimedia files such as images and videos. Steganography can offer a way of exchanging secret and encrypted information in an untypical mechanism where communicating parties can only interpret the secret message. The literature has shown a great interest in the least significant bit (LSB) technique which aims at embedding the secret message bits into the most insignificant bits of the image pixels. Although LSB showed a stable performance of image steganography yet, many works should be done on the message part. This paper aims to propose a combination of LSB and Deflate compression algorithm for image steganography. The proposed Deflate algorithm utilized both LZ77 and Huffman coding. After compressing the message text, LSB has been applied to embed the text within the cover image. Using benchmark images, the proposed method demonstrated an outperformance over the state of the art. This can proof the efficacy of using Deflate as a data compression prior to the LSB embedding.

Publisher

Institute of Advanced Engineering and Science

Subject

Electrical and Electronic Engineering,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. An Effect of Huffman Encoding with Hybrid Edge Detection in LSB Image Steganography;2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA);2024-05-19

2. An Enhanced Method to Secure the High Embedding Capacity Steganography Based on LSB Indicator;2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA);2024-05-19

3. Using Artificial Neural Network to Test Image Covert Communication Effect;Journal of Advances in Information Technology;2023

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