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Symmetry
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Symmetry and Asymmetry in Information Security and Network Security
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Symmetry and Asymmetry in Information Security and Network Security

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 3285

Special Issue Editor

Dr. Bingwen Feng

E-Mail Website
Guest Editor
College of Information Science and Technology, Jinan University, Guangzhou 510632, China
Interests: big data

Special Issue Information

Dear Colleagues,

Symmetry plays an important role in network security and data hiding. Embedded secret information is usually characterized as hidden patterns in information hiding. The analysis of hiding patterns can help understand and evaluate the security of data hiding methods applied to communication networks. The symmetry and asymmetry of hidden patterns can conveniently describe and realize the covert communication channel. The study of detection and correction of hidden patterns is crucial for complex network data hiding approaches. Configurate data hiding techniques to optimize the hidden patterns is promising for the security properties of practical network data hiding such as robustness, undetectability, capacity, etc. Therefore, understanding the symmetry and asymmetry of hidden patterns and their impact on the performance of network covert channels is essential. Overall, the use of symmetry and the understanding of data hiding techniques can help to improve network security.

Please note that all submitted papers must be within the general scope of the Symmetry journal.

Dr. Bingwen Feng
Guest Editor

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

  • network security
  • data hiding
  • information security

Published Papers (4 papers)

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Research

26 pages, 3409 KiB  
Article
AntiPhishStack: LSTM-Based Stacked Generalization Model for Optimized Phishing URL Detection
by Saba Aslam, Hafsa Aslam, Arslan Manzoor, Hui Chen and Abdur Rasool
Symmetry 2024, 16(2), 248; https://doi.org/10.3390/sym16020248 - 17 Feb 2024
Viewed by 935
Abstract
The escalating reliance on revolutionary online web services has introduced heightened security risks, with persistent challenges posed by phishing despite extensive security measures. Traditional phishing systems, reliant on machine learning and manual features, struggle with evolving tactics. Recent advances in deep learning offer [...] Read more.
The escalating reliance on revolutionary online web services has introduced heightened security risks, with persistent challenges posed by phishing despite extensive security measures. Traditional phishing systems, reliant on machine learning and manual features, struggle with evolving tactics. Recent advances in deep learning offer promising avenues for tackling novel phishing challenges and malicious URLs. This paper introduces a two-phase stack generalized model named AntiPhishStack, designed to detect phishing sites. The model leverages the learning of URLs and character-level TF-IDF features symmetrically, enhancing its ability to combat emerging phishing threats. In Phase I, features are trained on a base machine learning classifier, employing K-fold cross-validation for robust mean prediction. Phase II employs a two-layered stacked-based LSTM network with five adaptive optimizers for dynamic compilation, ensuring premier prediction on these features. Additionally, the symmetrical predictions from both phases are optimized and integrated to train a meta-XGBoost classifier, contributing to a final robust prediction. The significance of this work lies in advancing phishing detection with AntiPhishStack, operating without prior phishing-specific feature knowledge. Experimental validation on two benchmark datasets, comprising benign and phishing or malicious URLs, demonstrates the model’s exceptional performance, achieving a notable 96.04% accuracy compared to existing studies. This research adds value to the ongoing discourse on symmetry and asymmetry in information security and provides a forward-thinking solution for enhancing network security in the face of evolving cyber threats. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Information Security and Network Security)
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27 pages, 3690 KiB  
Article
RG-Based Region Incrementing Visual Cryptography with Abilities of OR and XOR Decryption
by Yu-Ru Lin and Justie Su-Tzu Juan
Symmetry 2024, 16(2), 153; https://doi.org/10.3390/sym16020153 - 28 Jan 2024
Cited by 1 | Viewed by 610
Abstract
Visual cryptography (VC) is a cryptographic technique that allows the encryption of a secret image into multiple shares. When the shares of a qualified subset are superimposed, the original secret image can be visually recovered. Region incremental visual cryptography (RIVC) is a class [...] Read more.
Visual cryptography (VC) is a cryptographic technique that allows the encryption of a secret image into multiple shares. When the shares of a qualified subset are superimposed, the original secret image can be visually recovered. Region incremental visual cryptography (RIVC) is a class of visual cryptography; it encrypts a single image into a shared image with multiple levels of secrecy, and when decrypted, the secret image of each region can be gradually recovered. Traditional VC encrypts two black-and-white images, and its recovery method is equivalent to a logical OR operation. To obtain a better recognizability of the restored image, the XORoperator becomes a simple and efficient method of encryption and decryption. Because the XOR operation needs extra cost or equipment, if the equipment cannot be obtained, the scheme can be more flexible if the secret can still be restored by using OR decryption (superimpose). In this paper, we propose a novel RIVC that allows encoding multiple secret regions of a secret image into n random grids. Both the OR operation and the XOR operation can be used as operations during decryption. The proposed scheme is evaluated by simulation, and the experimental result shows its correctness, effectiveness and practicability. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Information Security and Network Security)
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12 pages, 2409 KiB  
Article
A High-Payload Data Hiding Scheme Based on Absolute Moment Block Truncation Coding for Minimizing Hiding Impact
by Chia-Chen Lin, Bohan Zhang, Wei-Liang Tai, Pei-Feng Shiu and Jinn-Ke Jan
Symmetry 2024, 16(1), 64; https://doi.org/10.3390/sym16010064 - 4 Jan 2024
Viewed by 726
Abstract
Data hiding encompasses a wide range of applications related to hiding messages in digital images. The visual redundancy of images makes it possible to embed data in the images without attracting attention. Increasing the hiding capacity and decreasing the hiding distortion are prime [...] Read more.
Data hiding encompasses a wide range of applications related to hiding messages in digital images. The visual redundancy of images makes it possible to embed data in the images without attracting attention. Increasing the hiding capacity and decreasing the hiding distortion are prime objectives that data hiding intends to achieve. In this paper, we propose a high-payload data hiding scheme based on absolute moment block truncation coding (AMBTC) to minimize the impact of hiding. A two-level minimum mean square error (MMSE) quantizer generated by AMBTC is used to decrease the distortion associated with hiding. Also, we present a lookup table based on the symmetric property for adaptively hiding secrets in pixels to achieve high hiding capacity. We can embed almost 1.9 bits per pixel (bpp) with a high image quality of an average of 31 dB. Only 5.3% of pixels are changed during the data-hiding process. Compared with other schemes, we can use 1 bpp more relative payload for embedding with the same stego image quality. The experimental results show that the proposed scheme has better hiding performance because it allows a huge amount of secret data to be hidden while maintaining the high visual quality of the stego image. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Information Security and Network Security)
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15 pages, 4438 KiB  
Article
On the Design of Multi-Party Reversible Data Hiding over Ciphered Overexposed Images
by Bing Chen, Ranran Yang, Wanhan Fang, Xiuye Zhan and Jun Cai
Symmetry 2024, 16(1), 45; https://doi.org/10.3390/sym16010045 - 29 Dec 2023
Viewed by 645
Abstract
Multi-party reversible data hiding over ciphered images (MRDH-CI) has high restorability since the image is split into multiple ciphered images by secret sharing. However, the MRDH-CI methods either fail to produce satisfied results, or only work well for conventional images. This paper introduces [...] Read more.
Multi-party reversible data hiding over ciphered images (MRDH-CI) has high restorability since the image is split into multiple ciphered images by secret sharing. However, the MRDH-CI methods either fail to produce satisfied results, or only work well for conventional images. This paper introduces a multi-party reversible data-hiding approach over ciphered overexposed images. First, the pixels of the overexposed images are decomposed into two parts, each of which can be used for secret sharing. Then, the decomposed overexposed images are converted into multiple ciphered overexposed images by using a modified secret sharing method, in which the differences of the ciphered overexposed images are retained. The symmetry of the difference retaining makes the secret data conceal within the ciphered overexposed images such that the marked ciphered overexposed images can be created. Finally, by collecting sufficient marked ciphered overexposed images, it is possible to symmetrically reconstruct the concealed data and primitive overexposed image. Experimental results illustrate that the presented method can efficiently deal with overexposed images while maintaining a low computational overhead. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Information Security and Network Security)
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