Visible to the public A Novel Steganography Algorithm using Edge Detection and MPC Algorithm

TitleA Novel Steganography Algorithm using Edge Detection and MPC Algorithm
Publication TypeConference Paper
Year of Publication2019
AuthorsRezaei, Aref, Farzinvash, Leili, Farzamnia, Ali
Conference Name2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC)
Date PublishedAug. 2019
PublisherIEEE
ISBN Number978-1-7281-4374-3
Keywordscomposability, confidential data, corner pixels, cover image, data concealment, data embedding process, digital images, edge blocks, edge detection, edge detection scheme, full tree, Image coding, Internet, LSB, LSB algorithm, Metrics, MPC, MPC algorithm, PSNR, pubcrawl, Resiliency, Scalability, security, sharp edges, steganography, steganography algorithm, steganography techniques, stego image, trees (mathematics)
Abstract

With the rapid development of the Internet, preserving the security of confidential data has become a challenging issue. An effective method to this end is to apply steganography techniques. In this paper, we propose an efficient steganography algorithm which applies edge detection and MPC algorithm for data concealment in digital images. The proposed edge detection scheme partitions the given image, namely cover image, into blocks. Next, it identifies the edge blocks based on the variance of their corner pixels. Embedding the confidential data in sharp edges causes less distortion in comparison to the smooth areas. To diminish the imposed distortion by data embedding in edge blocks, we employ LSB and MPC algorithms. In the proposed scheme, the blocks are split into some groups firstly. Next, a full tree is constructed per group using the LSBs of its pixels. This tree is converted into another full tree in some rounds. The resultant tree is used to modify the considered LSBs. After the accomplishment of the data embedding process, the final image, which is called stego image, is derived. According to the experimental results, the proposed algorithm improves PSNR with at least 5.4 compared to the previous schemes.

URLhttps://ieeexplore.ieee.org/document/8985150
DOI10.1109/ISCISC48546.2019.8985150
Citation Keyrezaei_novel_2019