Symmetry in Image Encryption
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1022
Special Issue Editors
Interests: image processing; computer vision; data science
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the era of digital communication and information security, the preservation of data integrity and confidentiality is paramount. Among others, images are a fundamental and a significant data source in various domains, from healthcare, finance to military and personal communication.
This Special Issue, ‘Symmetry in Image Encryption’ seeks to underscore the intersection and role of symmetry principles, cryptographic techniques, and deep learning in protecting visual information. We invite researchers, practitioners, and experts working in this domain to submit their papers (original research as well as theoretical studies) that uses novel methods, particularly deep learning, to address the symmetrical aspects of image encryption and uncover potential vulnerabilities, thereby contributing to the practical implementation of symmetry-based image encryption techniques.
Potential topics include the following:
- Symmetric Cryptographic Algorithms: Investigate the role of symmetric encryption algorithms in securing image data and explore their strengths and limitations, including how deep learning can enhance their effectiveness;
- Visual Symmetry Analysis: Explore techniques for detecting and leveraging inherent symmetries within images for encryption and decryption processes, with a focus on how deep learning can aid in this analysis;
- Security and Robustness: Discuss the security challenges and potential vulnerabilities associated with symmetric image encryption methods, and propose strategies for enhancing robustness, including the integration of deep learning techniques;
- Deep Learning Applications: Highlight practical applications of deep learning in symmetric image encryption, showcasing innovative approaches that leverage neural networks for enhanced security;
- Emerging Trends: Explore emerging trends, innovations, and future directions in the field of image encryption, with a focus on the synergies between deep learning and symmetry-related concepts.
Dr. Sabri My Abdelouahed
Dr. Yahyaouy Ali
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- image encryption
- symmetric cryptography
- encryption vulnerabilities
- image protection
- image privacy
- symmetry-based encryption
- symmetric key cryptography
- robust encryption
- visual information security
- cryptographic techniques
- symmetry-based decryption
- deep learning for image encryption
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