A novel visually meaningful image encryption algorithm based on parallel compressive sensing and adaptive embedding. (15th December 2022)
- Record Type:
- Journal Article
- Title:
- A novel visually meaningful image encryption algorithm based on parallel compressive sensing and adaptive embedding. (15th December 2022)
- Main Title:
- A novel visually meaningful image encryption algorithm based on parallel compressive sensing and adaptive embedding
- Authors:
- Wang, Xingyuan
Liu, Cheng
Jiang, Donghua - Abstract:
- Highlights: The eigenvalue value of the plain image is used as a part of the key. Decreasing computational complexity and storage space. Find the best embedding position adaptively. Abstract: Compared with traditional image encryption algorithms that generate noise-like images, visually meaningful image encryption achieves the dual protection of digital images in content and vision, but the embedded position is often fixed or controlled by keys. If the embedding position is not appropriate, the effect of encryption and decryption will be affected to a certain extent. In this paper, a novel visually meaningful image encryption and adaptive embedding scheme is proposed by using chaotic cellular neural network (CCNN), parallel compressive sensing (PCS), and least significant bit (LSB) embedding in transform domain. First, 2D discrete wavelet transform (DWT) is used to sparse the plain image. Then, the sparse matrix after threshold processing is encrypted and measured by local binary pattern (LBP) and PCS technology. Finally, the information entropy is used to analyze the texture degree of the carrier image for adaptive embedding, so as to obtain the visually meaningful cipher image. Moreover, the ability of the algorithm to resist known- and chosen- plaintext attacks is improved by using the plaintext eigenvalue as part of the encryption key stream. Considering the practicability of the scheme, the plaintext eigenvalue is hidden in the visually meaningful cipher image, whichHighlights: The eigenvalue value of the plain image is used as a part of the key. Decreasing computational complexity and storage space. Find the best embedding position adaptively. Abstract: Compared with traditional image encryption algorithms that generate noise-like images, visually meaningful image encryption achieves the dual protection of digital images in content and vision, but the embedded position is often fixed or controlled by keys. If the embedding position is not appropriate, the effect of encryption and decryption will be affected to a certain extent. In this paper, a novel visually meaningful image encryption and adaptive embedding scheme is proposed by using chaotic cellular neural network (CCNN), parallel compressive sensing (PCS), and least significant bit (LSB) embedding in transform domain. First, 2D discrete wavelet transform (DWT) is used to sparse the plain image. Then, the sparse matrix after threshold processing is encrypted and measured by local binary pattern (LBP) and PCS technology. Finally, the information entropy is used to analyze the texture degree of the carrier image for adaptive embedding, so as to obtain the visually meaningful cipher image. Moreover, the ability of the algorithm to resist known- and chosen- plaintext attacks is improved by using the plaintext eigenvalue as part of the encryption key stream. Considering the practicability of the scheme, the plaintext eigenvalue is hidden in the visually meaningful cipher image, which reduces unnecessary key transmission. Experimental results show that the scheme is effective on the premise of visual security and decryption quality. … (more)
- Is Part Of:
- Expert systems with applications. Volume 209(2022)
- Journal:
- Expert systems with applications
- Issue:
- Volume 209(2022)
- Issue Display:
- Volume 209, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 209
- Issue:
- 2022
- Issue Sort Value:
- 2022-0209-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12-15
- Subjects:
- Image compression and encryption -- Chaotic cellular neural network -- Parallel compressive sensing -- Wavelet transform -- Visually meaningful cipher image
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2022.118426 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23342.xml