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J. Imaging
Special Issues
Visualisation and Cybersecurity
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Visualisation and Cybersecurity

A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Visualization and Computer Graphics".

Deadline for manuscript submissions: closed (11 December 2022) | Viewed by 16355

Special Issue Editors

Dr. Yang-Wai Chow

E-Mail Website
Guest Editor
School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
Interests: virtual reality; multimedia security; adversarial machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Jongkil Kim

E-Mail Website
Guest Editor
School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
Interests: network security; data driven security; cryptography
Dr. Ngoc Thuy Le

E-Mail Website
Guest Editor
School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
Interests: cybersecurity; cloud security; machine learning

Special Issue Information

Dear Colleagues,

The growing sophistication of cyber attacks has made it increasingly challenging to secure data and systems against security breaches. Visualisation plays a key role in cybersecurity as it allows complex data to be presented and analysed in an intuitive form. The application of visualisation in cybersecurity gives rise to a variety of uses and benefits. It supports human understanding and capacity to map out threat surfaces, allows users to intuitively analyse and identify patterns in data, creates situation awareness in cybersecurity by visualising data from different sources, allows for security techniques such as visual cryptography, and so on. Cybersecurity visualisation covers a broad range of disciplines, including human aspects such as visualisation and visual perception, and technical aspects such as data analytics, computer vision, image processing, machine learning and network security.

This Special Issue welcomes a broad spectrum of papers ranging from innovative techniques and applications to position papers and comprehensive reviews, involving research on visualisation and cybersecurity. We seek original and high-quality submissions that are related, but not limited, to topics including security visualisation, data visualisation, visualisation in artificial intelligence, adversarial machine learning in the visual domain, computer vision for cybersecurity, visual cryptography and secret sharing, digital watermarking, CAPTCHA, visualisation for situation awareness and malware visualisation.

Dr. Yang-Wai Chow
Dr. Jongkil Kim
Dr. Ngoc Thuy Le
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. Journal of Imaging 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 1800 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

  • security visualisation
  • data visualisation
  • visualisation in artificial intelligence
  • adversarial machine learning in the visual domain
  • computer vision for cybersecurity
  • visual cryptography and secret sharing
  • digital watermarking
  • CAPTCHA
  • visualisation for situation awareness
  • malware visualisation

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Published Papers (4 papers)

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Research

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10 pages, 726 KiB  
Article
A Study of the Information Embedding Method into Raster Image Based on Interpolation
by Elmira Daiyrbayeva, Aigerim Yerimbetova, Ivan Nechta, Ekaterina Merzlyakova, Ainur Toigozhinova and Almas Turganbayev
J. Imaging 2022, 8(10), 288; https://doi.org/10.3390/jimaging8100288 - 19 Oct 2022
Cited by 5 | Viewed by 1650
Abstract
This article is devoted to the study of the improved neighbor mean interpolation (INMI) steganographic method. To date, no steganalysis of such a method of information embedding has been carried out. We implemented the INMI method of embedding messages in raster files and [...] Read more.
This article is devoted to the study of the improved neighbor mean interpolation (INMI) steganographic method. To date, no steganalysis of such a method of information embedding has been carried out. We implemented the INMI method of embedding messages in raster files and conducted a stegoanalysis on a set of 800 images of 225 × 225 size. Experimentally, we found that with this embedding method, the maximum container capacity is 21% and that it depends on the contents of the container. It is established that only 60 files out of 800 actually have the maximum capacity. We presented the calculation of the Type I error and the percentage of information detection in the obtained containers by the regular–singular (RS) method. The results showed that the considered steganographic algorithm is resistant to RS steganalysis and is comparable to the stegosystem of the permutation method investigated in one of our previous articles. Full article
(This article belongs to the Special Issue Visualisation and Cybersecurity)
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13 pages, 745 KiB  
Article
Secure Image Encryption Using Chaotic, Hybrid Chaotic and Block Cipher Approach
by Nirmal Chaudhary, Tej Bahadur Shahi and Arjun Neupane
J. Imaging 2022, 8(6), 167; https://doi.org/10.3390/jimaging8060167 - 10 Jun 2022
Cited by 29 | Viewed by 4624
Abstract
Secure image transmission is one of the most challenging problems in the age of communication technology. Millions of people use and transfer images for either personal or commercial purposes over the internet. One way of achieving secure image transmission over the network is [...] Read more.
Secure image transmission is one of the most challenging problems in the age of communication technology. Millions of people use and transfer images for either personal or commercial purposes over the internet. One way of achieving secure image transmission over the network is encryption techniques that convert the original image into a non-understandable or scrambled form, called a cipher image, so that even if the attacker gets access to the cipher they would not be able to retrieve the original image. In this study, chaos-based image encryption and block cipher techniques are implemented and analyzed for image encryption. Arnold cat map in combination with a logistic map are used as native chaotic and hybrid chaotic approaches respectively whereas advanced encryption standard (AES) is used as a block cipher approach. The chaotic and AES methods are applied to encrypt images and are subjected to measures of different performance parameters such as peak signal to noise ratio (PSNR), number of pixels change rate (NPCR), unified average changing intensity (UACI), and histogram and computation time analysis to measure the strength of each algorithm. The results show that the hybrid chaotic map has better NPCR and UACI values which makes it more robust to differential attacks or chosen plain text attacks. The Arnold cat map is computationally efficient in comparison to the other two approaches. However, AES has a lower PSNR value (7.53 to 11.93) and has more variation between histograms of original and cipher images, thereby indicating that it is more resistant to statistical attacks than the other two approaches. Full article
(This article belongs to the Special Issue Visualisation and Cybersecurity)
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23 pages, 5783 KiB  
Article
Are Social Networks Watermarking Us or Are We (Unawarely) Watermarking Ourself?
by Flavio Bertini, Rajesh Sharma and Danilo Montesi
J. Imaging 2022, 8(5), 132; https://doi.org/10.3390/jimaging8050132 - 10 May 2022
Cited by 7 | Viewed by 2637
Abstract
In the last decade, Social Networks (SNs) have deeply changed many aspects of society, and one of the most widespread behaviours is the sharing of pictures. However, malicious users often exploit shared pictures to create fake profiles, leading to the growth of cybercrime. [...] Read more.
In the last decade, Social Networks (SNs) have deeply changed many aspects of society, and one of the most widespread behaviours is the sharing of pictures. However, malicious users often exploit shared pictures to create fake profiles, leading to the growth of cybercrime. Thus, keeping in mind this scenario, authorship attribution and verification through image watermarking techniques are becoming more and more important. In this paper, we firstly investigate how thirteen of the most popular SNs treat uploaded pictures in order to identify a possible implementation of image watermarking techniques by respective SNs. Second, we test the robustness of several image watermarking algorithms on these thirteen SNs. Finally, we verify whether a method based on the Photo-Response Non-Uniformity (PRNU) technique, which is usually used in digital forensic or image forgery detection activities, can be successfully used as a watermarking approach for authorship attribution and verification of pictures on SNs. The proposed method is sufficiently robust, in spite of the fact that pictures are often downgraded during the process of uploading to the SNs. Moreover, in comparison to conventional watermarking methods the proposed method can successfully pass through different SNs, solving related problems such as profile linking and fake profile detection. The results of our analysis on a real dataset of 8400 pictures show that the proposed method is more effective than other watermarking techniques and can help to address serious questions about privacy and security on SNs. Moreover, the proposed method paves the way for the definition of multi-factor online authentication mechanisms based on robust digital features. Full article
(This article belongs to the Special Issue Visualisation and Cybersecurity)
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Review

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15 pages, 701 KiB  
Review
Visualization and Cybersecurity in the Metaverse: A Survey
by Yang-Wai Chow, Willy Susilo, Yannan Li, Nan Li and Chau Nguyen
J. Imaging 2023, 9(1), 11; https://doi.org/10.3390/jimaging9010011 - 31 Dec 2022
Cited by 29 | Viewed by 6572
Abstract
The popularity of the Metaverse has rapidly increased in recent years. However, despite the attention, investment, and promise of the Metaverse, there are various cybersecurity issues that must be addressed before the Metaverse can truly be adopted in practice for serious applications. The [...] Read more.
The popularity of the Metaverse has rapidly increased in recent years. However, despite the attention, investment, and promise of the Metaverse, there are various cybersecurity issues that must be addressed before the Metaverse can truly be adopted in practice for serious applications. The realization of the Metaverse is envisioned by many as requiring the use of visualization technologies such as Virtual Reality (VR) and Augmented Reality (AR). This visual aspect of the Metaverse will undoubtedly give rise to emerging cybersecurity threats that have not received much attention. As such, the purpose of this survey is to investigate cybersecurity threats faced by the Metaverse in relation to visualization technologies. Furthermore, this paper discusses existing work and open research directions on the development of countermeasures against such threats. As the Metaverse is a multidisciplinary topic, the intention of this work is to provide a background of the field to aid researchers in related areas. Full article
(This article belongs to the Special Issue Visualisation and Cybersecurity)
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