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Challenges and Innovations in Multimedia Encryption and Information Security

Submission Deadline: 31 August 2025 View: 2178 Submit to Special Issue

Guest Editors

Dr. Jawad Ahmad, Edinburgh Napier University, UK
Dr. Muazzam A Khan, Quaid-i-Azam University, Pakistan
Dr. Wadii Boulila, Prince Sultan University, Saudi Arabia

Summary

Multimedia data are becoming increasingly important in today's digital world, driven by the wide range of computer applications and corresponding technologies. With the advent of 5th generation (5G) technology, digital images are frequently transmitted via open, insecure channels on the Internet. As a result, the security of digital image data is significantly compromised by recent advancements in computer-related technologies. Several state-of-the-art encryption techniques have been introduced to address these security issues. Unfortunately, many algorithms have been developed specifically for text encryption, rendering most traditional encryption schemes inappropriate for encrypting digital images. This is because text encryption techniques are not suitable for image data, due to several unique characteristics, including large volumes of data and a strong correlation between pixel values. In this context, we invite academics and industry to contribute original research articles and review articles that seek to discover innovative solutions for multimedia encryption and information security.

Keywords

Image Encryption; Information Security; Cybersecurity; Cryptography; Network Security; Internet of Things; Machine Learning for Cybersecurity

Published Papers

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Open Access

ARTICLE

Face Forgery Detection via Multi-Scale Dual-Modality Mutual Enhancement Network
Yuanqing Ding, Hanming Zhai, Qiming Ma, Liang Zhang, Lei Shao, Fanliang Bu
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.066307
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract As the use of deepfake facial videos proliferate, the associated threats to social security and integrity cannot be overstated. Effective methods for detecting forged facial videos are thus urgently needed. While many deep learning-based facial forgery detection approaches show promise, they often fail to delve deeply into the complex relationships between image features and forgery indicators, limiting their effectiveness to specific forgery techniques. To address this challenge, we propose a dual-branch collaborative deepfake detection network. The network processes video frame images as input, where a specialized noise extraction module initially extracts the noise feature maps.… More >

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ARTICLE

Tamper Detection in Multimodal Biometric Templates Using Fragile Watermarking and Artificial Intelligence
Fatima Abu Siryeh, Hussein Alrammahi, Abdullahi Abdu İbrahim
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.065206
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract Biometric template protection is essential for finger-based authentication systems, as template tampering and adversarial attacks threaten the security. This paper proposes a DCT-based fragile watermarking scheme incorporating AI-based tamper detection to improve the integrity and robustness of finger authentication. The system was tested against NIST SD4 and Anguli fingerprint datasets, wherein 10,000 watermarked fingerprints were employed for training. The designed approach recorded a tamper detection rate of 98.3%, performing 3–6% better than current DCT, SVD, and DWT-based watermarking approaches. The false positive rate (≤1.2%) and false negative rate (≤1.5%) were much lower compared to previous… More >

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ARTICLE

Privacy Preserving Federated Anomaly Detection in IoT Edge Computing Using Bayesian Game Reinforcement Learning
Fatima Asiri, Wajdan Al Malwi, Fahad Masood, Mohammed S. Alshehri, Tamara Zhukabayeva, Syed Aziz Shah, Jawad Ahmad
CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3943-3960, 2025, DOI:10.32604/cmc.2025.066498
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract Edge computing (EC) combined with the Internet of Things (IoT) provides a scalable and efficient solution for smart homes. The rapid proliferation of IoT devices poses real-time data processing and security challenges. EC has become a transformative paradigm for addressing these challenges, particularly in intrusion detection and anomaly mitigation. The widespread connectivity of IoT edge networks has exposed them to various security threats, necessitating robust strategies to detect malicious activities. This research presents a privacy-preserving federated anomaly detection framework combined with Bayesian game theory (BGT) and double deep Q-learning (DDQL). The proposed framework integrates BGT… More >

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ARTICLE

A Robust Image Watermarking Based on DWT and RDWT Combined with Möbius Transformations
Atheer Alrammahi, Hedieh Sajedi
CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 887-918, 2025, DOI:10.32604/cmc.2025.063866
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract Ensuring digital media security through robust image watermarking is essential to prevent unauthorized distribution, tampering, and copyright infringement. This study introduces a novel hybrid watermarking framework that integrates Discrete Wavelet Transform (DWT), Redundant Discrete Wavelet Transform (RDWT), and Möbius Transformations (MT), with optimization of transformation parameters achieved via a Genetic Algorithm (GA). By combining frequency and spatial domain techniques, the proposed method significantly enhances both the imperceptibility and robustness of watermark embedding. The approach leverages DWT and RDWT for multi-resolution decomposition, enabling watermark insertion in frequency subbands that balance visibility and resistance to attacks. RDWT,… More >

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ARTICLE

Advanced Techniques for Dynamic Malware Detection and Classification in Digital Security Using Deep Learning
Taher Alzahrani
CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4575-4606, 2025, DOI:10.32604/cmc.2025.063448
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract The rapid evolution of malware presents a critical cybersecurity challenge, rendering traditional signature-based detection methods ineffective against novel variants. This growing threat affects individuals, organizations, and governments, highlighting the urgent need for robust malware detection mechanisms. Conventional machine learning-based approaches rely on static and dynamic malware analysis and often struggle to detect previously unseen threats due to their dependency on predefined signatures. Although machine learning algorithms (MLAs) offer promising detection capabilities, their reliance on extensive feature engineering limits real-time applicability. Deep learning techniques mitigate this issue by automating feature extraction but may introduce computational overhead,… More >

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ARTICLE

Weighted Attribute Based Conditional Proxy Re-Encryption in the Cloud
Xixi Yan, Jing Zhang, Pengyu Cheng
CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1399-1414, 2025, DOI:10.32604/cmc.2025.059969
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract Conditional proxy re-encryption (CPRE) is an effective cryptographic primitive language that enhances the access control mechanism and makes the delegation of decryption permissions more granular, but most of the attribute-based conditional proxy re-encryption (AB-CPRE) schemes proposed so far do not take into account the importance of user attributes. A weighted attribute-based conditional proxy re-encryption (WAB-CPRE) scheme is thus designed to provide more precise decryption rights delegation. By introducing the concept of weight attributes, the quantity of system attributes managed by the server is reduced greatly. At the same time, a weighted tree structure is constructed… More >

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ARTICLE

HybridEdge: A Lightweight and Secure Hybrid Communication Protocol for the Edge-Enabled Internet of Things
Amjad Khan, Rahim Khan, Fahad Alturise, Tamim Alkhalifah
CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3161-3178, 2025, DOI:10.32604/cmc.2025.060372
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the… More >

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REVIEW

Enhancing Deepfake Detection: Proactive Forensics Techniques Using Digital Watermarking
Zhimao Lai, Saad Arif, Cong Feng, Guangjun Liao, Chuntao Wang
CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 73-102, 2025, DOI:10.32604/cmc.2024.059370
（This article belongs to the Special Issue: Challenges and Innovations in Multimedia Encryption and Information Security)
Abstract With the rapid advancement of visual generative models such as Generative Adversarial Networks (GANs) and stable Diffusion, the creation of highly realistic Deepfake through automated forgery has significantly progressed. This paper examines the advancements in Deepfake detection and defense technologies, emphasizing the shift from passive detection methods to proactive digital watermarking techniques. Passive detection methods, which involve extracting features from images or videos to identify forgeries, encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics. In contrast, proactive digital watermarking techniques embed specific markers into images or videos, facilitating More >

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Challenges and Innovations in Multimedia Encryption and Information Security

Guest Editors

Summary

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