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Real-Time Technique in Multimedia Security and Content Protection
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Real-Time Technique in Multimedia Security and Content Protection

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 January 2022) | Viewed by 18042

Special Issue Editor

Prof. Dr. Cheonshik Kim

E-Mail Website
Guest Editor
Department of Computer Engineering, Sejong University, Seoul 05006, Korea
Interests: multimedia security; multimedia signal processing; image compression; watermark technology; steganography; multimedia database
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the development of smart devices (including smartphones), we can live in an environment where various forms of multimedia can be easily used. In addition, advances in software and hardware, including 5G, are expected to enable us to use faster and more sophisticated multimedia.

Multimedia applications in which Real-Time Technique (RTT) is used include the following.

  • RTT multimedia security (watermark, encryption, …);
  • RTT mobile multimedia systems and services; Security, privacy, and cryptographic protocol;
  • RTT network security issues and protocols;
  • RTT key management and authentication;
  • RTT authentication and access control;
  • RTT intrusion detection and prevention;
  • RTT content protection and digital rights management;
  • RTT trusted computing;
  • RTT information hiding;
  • RTT biometrics;
  • RTT computer vision;
  • RTT video and image compression.

Prof. Dr. Cheonshik Kim
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. Applied Sciences is an international peer-reviewed open access semimonthly 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

  • security
  • privacy
  • authentication
  • cryptographic protocol
  • content protection
  • biometrics
  • biosensor

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Published Papers (4 papers)

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Research

18 pages, 3520 KiB  
Article
Image Forensics Using Non-Reducing Convolutional Neural Network for Consecutive Dual Operators
by Se-Hyun Cho, Saurabh Agarwal, Seok-Joo Koh and Ki-Hyun Jung
Appl. Sci. 2022, 12(14), 7152; https://doi.org/10.3390/app12147152 - 15 Jul 2022
Cited by 4 | Viewed by 1694
Abstract
Digital image forensics has become necessary as an emerging technology. Images can be adulterated effortlessly using image tools. The latest techniques are available to detect whether an image is adulterated by a particular operator. Most of the existing techniques are suitable for high [...] Read more.
Digital image forensics has become necessary as an emerging technology. Images can be adulterated effortlessly using image tools. The latest techniques are available to detect whether an image is adulterated by a particular operator. Most of the existing techniques are suitable for high resolution and manipulated images by a single operator. In a real scenario, multiple operators are applied to manipulate the image many times. In this paper, a robust moderate-sized convolutional neural network is proposed to identify manipulation operators and also the operator’s sequence for two operators in particular. The proposed bottleneck approach is used to make the network deeper and reduce the computational cost. Only one pooling layer, called a global averaging pooling layer, is utilized to retain the maximum flow of information and to avoid the overfitting issue between the layers. The proposed network is also robust against low resolution and JPEG compressed images. Even though the detection of the operator is challenging due to the limited availability of statistical information in low resolution and JPEG compressed images, the proposed model can also detect an operator with different parameters and compression quality factors that are not considered in training. Full article
(This article belongs to the Special Issue Real-Time Technique in Multimedia Security and Content Protection)
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20 pages, 4014 KiB  
Article
Multimodal Biometric Template Protection Based on a Cancelable SoftmaxOut Fusion Network
by Jihyeon KIM, Yoon Gyo Jung and Andrew Beng Jin Teoh
Appl. Sci. 2022, 12(4), 2023; https://doi.org/10.3390/app12042023 - 15 Feb 2022
Cited by 17 | Viewed by 2730
Abstract
Authentication systems that employ biometrics are commonplace, as they offer a convenient means of authenticating an individual’s identity. However, these systems give rise to concerns about security and privacy due to insecure template management. As a remedy, biometric template protection (BTP) has been [...] Read more.
Authentication systems that employ biometrics are commonplace, as they offer a convenient means of authenticating an individual’s identity. However, these systems give rise to concerns about security and privacy due to insecure template management. As a remedy, biometric template protection (BTP) has been developed. Cancelable biometrics is a non-invertible form of BTP in which the templates are changeable. This paper proposes a deep-learning-based end-to-end multimodal cancelable biometrics scheme called cancelable SoftmaxOut fusion network (CSMoFN). By end-to-end, we mean a model that receives raw biometric data as input and produces a protected template as output. CSMoFN combines two biometric traits, the face and the periocular region, and is composed of three modules: a feature extraction and fusion module, a permutation SoftmaxOut transformation module, and a multiplication-diagonal compression module. The first module carries out feature extraction and fusion, while the second and third are responsible for the hashing of fused features and compression. In addition, our network is equipped with dual template-changeability mechanisms with user-specific seeded permutation and binary random projection. CSMoFN is trained by minimizing the ArcFace loss and the pairwise angular loss. We evaluate the network, using six face–periocular multimodal datasets, in terms of its verification performance, unlinkability, revocability, and non-invertibility. Full article
(This article belongs to the Special Issue Real-Time Technique in Multimedia Security and Content Protection)
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24 pages, 13625 KiB  
Article
Key Recovery for Content Protection Using Ternary PUFs Designed with Pre-Formed ReRAM
by Bertrand Francis Cambou and Saloni Jain
Appl. Sci. 2022, 12(4), 1785; https://doi.org/10.3390/app12041785 - 9 Feb 2022
Cited by 10 | Viewed by 2481
Abstract
Physical unclonable functions, embedded in terminal devices, can be used as part of the recovery process of session keys that protect digital files. Such an approach is only valuable when the physical element offers sufficient tamper resistance. Otherwise, error correcting codes should be [...] Read more.
Physical unclonable functions, embedded in terminal devices, can be used as part of the recovery process of session keys that protect digital files. Such an approach is only valuable when the physical element offers sufficient tamper resistance. Otherwise, error correcting codes should be able to handle any variations arising from aging, and environmentally induced drifts of the terminal devices. The ternary cryptographic protocols presented in this paper, leverage the physical properties of resistive random-access memories operating at extremely low power in the pre-forming range to create an additional level of security, while masking the most unstable cells during key generation cycles. The objective is to reach bit error rates below the 10−3 range from elements subjected to drifts and environmental effects. We propose replacing the error correcting codes with light search engines, that use ciphertexts as helper data to reduce information leakage. The tamper-resistant schemes discussed in the paper include: (i) a cell-pairing differential method to hide the physical parameters; (ii) an attack detection system and a low power self-destruct mode; (iii) a multi-factor authentication, information control, and a one-time read-only function. In the experimental section, we describe how prototypes were fabricated to test and quantify the performance of the suggested methods, using static random access memory devices as the benchmark. Full article
(This article belongs to the Special Issue Real-Time Technique in Multimedia Security and Content Protection)
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24 pages, 14514 KiB  
Article
Encrypted Network Traffic Analysis of Secure Instant Messaging Application: A Case Study of Signal Messenger App
by Asmara Afzal, Mehdi Hussain, Shahzad Saleem, M. Khuram Shahzad, Anthony T. S. Ho and Ki-Hyun Jung
Appl. Sci. 2021, 11(17), 7789; https://doi.org/10.3390/app11177789 - 24 Aug 2021
Cited by 15 | Viewed by 10325
Abstract
Instant messaging applications (apps) have played a vital role in online interaction, especially under COVID-19 lockdown protocols. Apps with security provisions are able to provide confidentiality through end-to-end encryption. Ill-intentioned individuals and groups use these security services to their advantage by using the [...] Read more.
Instant messaging applications (apps) have played a vital role in online interaction, especially under COVID-19 lockdown protocols. Apps with security provisions are able to provide confidentiality through end-to-end encryption. Ill-intentioned individuals and groups use these security services to their advantage by using the apps for criminal, illicit, or fraudulent activities. During an investigation, the provision of end-to-end encryption in apps increases the complexity for digital forensics investigators. This study aims to provide a network forensic strategy to identify the potential artifacts from the encrypted network traffic of the prominent social messenger app Signal (on Android version 9). The analysis of the installed app was conducted over fully encrypted network traffic. By adopting the proposed strategy, the forensic investigator can easily detect encrypted traffic activities such as chatting, media messages, audio, and video calls by looking at the payload patterns. Furthermore, a detailed analysis of the trace files can help to create a list of chat servers and IP addresses of involved parties in the events. As a result, the proposed strategy significantly facilitates extraction of the app’s behavior from encrypted network traffic which can then be used as supportive evidence for forensic investigation. Full article
(This article belongs to the Special Issue Real-Time Technique in Multimedia Security and Content Protection)
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