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Electronics
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Security and Privacy in Networks and Multimedia, 2nd Edition
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Security and Privacy in Networks and Multimedia, 2nd Edition

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 15 August 2026 | Viewed by 24629

Special Issue Editors

Dr. Tomasz Rak

E-Mail Website
Guest Editor
Department of Computer and Control Engineering, Rzeszow University of Technology, Powstancow Warszawy 12, Rzeszów, Poland
Interests: computer engineering; formal modeling and testing; distributed systems; cluster computing; systems modeling; network monitoring; network security; interactive systems; Web services; Internet systems architectures
Special Issues, Collections and Topics in MDPI journals
Dr. Dariusz Rzońca

E-Mail Website
Guest Editor
Department of Computer and Control Engineering, Rzeszow University of Technology, Powstancow Warszawy 12, Rzeszów, Poland
Interests: embedded systems; industrial control systems; cryptography; colored Petri nets
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the first edition of this Special Issue (https://www.mdpi.com/journal/electronics/special_issues/Q5660YL8P2), in the second edition, we continue to encourage all those interested in the topic to promote their vision and ideas.

This Special Issue intends to collect high-quality research and review articles concerning privacy protection and security in networks and multimedia processing. We also welcome academic articles that cover security and privacy policies related to IoT and multimedia services.

The topics of interest include, but are not limited to, the following:

  • New technological developments;
  • Security architectures and platforms;
  • Intrusion detection;
  • Anonymization techniques;
  • Access control;
  • AI security;
  • Multimedia services;
  • Processing of encrypted multimedia;
  • Privacy-preserving data mining;
  • Secure multimedia distribution in cloud computing;
  • Cryptographic protocols;
  • Security and privacy in online social networks;
  • Security and privacy issues in smart homes;
  • Empirical research and case studies;
  • Web application security.

Dr. Tomasz Rak
Dr. Dariusz Rzońca
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 250 words) can be sent to the Editorial Office for assessment.

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. Electronics 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
  • access control
  • cloud computing security
  • data mining security
  • security algorithms
  • data security for mobile internet and social networks
  • games for cybersecurity training and awareness
  • multimedia service
  • enhancement in web infrastructure
  • smart homes

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (6 papers)

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Research

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19 pages, 1739 KB  
Article
Implementing Post-Quantum Cryptography to Industrial Wireless Networks
by Mario Keh and Yuhua Chen
Electronics 2026, 15(9), 1834; https://doi.org/10.3390/electronics15091834 - 26 Apr 2026
Viewed by 161
Abstract
The purpose of this research is to introduce a scalable system of an improved security for devices connected to a wireless network using the Advanced Encryption Standard with a Post-Quantum Cryptography standard FIPS203, Module Lattice–Key Encapsulation Mechanism (ML-KEM). This implementation is to address [...] Read more.
The purpose of this research is to introduce a scalable system of an improved security for devices connected to a wireless network using the Advanced Encryption Standard with a Post-Quantum Cryptography standard FIPS203, Module Lattice–Key Encapsulation Mechanism (ML-KEM). This implementation is to address concerns regarding compromised network security or bad actors sniffing packets through a data bus to collect unintended compromised data. The ML-KEM is used to create a shared secret that is used as the symmetric key that will enable the encryption and decryption method for the ciphertexts between the client and the host. This research provides a baseline implementation of added security against Quantum Computers by using an encapsulation method for key pairs, digital signatures for data integrity, and added difficulties for side-channel attacks from unauthorized users. Devices that are older than the WiFi6-compliant standard also have additional vulnerability of not having the WiFi Protected Access (WPA) third-generation security, which this work addresses. This paper proposes an added layer of encryption security that is sufficient to protect information within the network that has been compromised by an unauthorized user. Based on the findings, new features, utilities and improvements are recommended that can modernize the needs of the industry. Full article
(This article belongs to the Special Issue Security and Privacy in Networks and Multimedia, 2nd Edition)
28 pages, 901 KB  
Article
PrivLocAuth: Enabling Location-Aware Cross-Domain UAV Authentication with Zero-Knowledge Location Privacy
by Shayesta Naziri, Xu Wang, Jian Xu, Christy Jie Liang and Guangsheng Yu
Electronics 2026, 15(6), 1243; https://doi.org/10.3390/electronics15061243 - 17 Mar 2026
Viewed by 419
Abstract
Secure cross-domain UAV authentication is challenging because identity verification alone is insufficient to guarantee safe operation. In many UAV applications, it is equally critical to verify that a UAV is currently located within an authorized geographic region. Existing approaches often expose precise GPS [...] Read more.
Secure cross-domain UAV authentication is challenging because identity verification alone is insufficient to guarantee safe operation. In many UAV applications, it is equally critical to verify that a UAV is currently located within an authorized geographic region. Existing approaches often expose precise GPS coordinates, rely on static identifiers that enable tracking, or fail to guarantee the freshness and authenticity of location evidence. These weaknesses allow replay, location spoofing, and trajectory inference attacks, especially in multi-domain environments. To address these limitations, we propose PrivLocAuth, a zero-knowledge-based cross-domain UAV authentication protocol that enforces geofence restrictions without revealing actual locations. In PrivLocAuth, UAVs encode their current coordinates into fresh Pedersen commitments, which are attested by the home Local Domain Server (LDS) using short-lived Schnorr signatures. Based on these attested commitments, UAVs generate Bulletproof range proofs to demonstrate compliance with cross-domain server-defined geofences. This design ensures that UAVs operate within authorized airspace while preserving strong location privacy. PrivLocAuth further incorporates a lightweight elliptic curve cryptography (ECC) and Schnorr signature-based credential framework that enables unlinkable authentication across-domains, preventing session correlation and identity tracking. Formal security analysis demonstrates resistance to impersonation, replay, geofence-bypass, and linkage attacks. Experimental evaluation shows low computational latency and minimal communication overhead, confirming the protocol’s suitability for resource-constrained UAV platforms operating in dynamic cross-domain environments. Full article
(This article belongs to the Special Issue Security and Privacy in Networks and Multimedia, 2nd Edition)
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18 pages, 683 KB  
Article
InMesh: A Zero-Configuration Agentless Endpoint Detection and Response System
by Angel Kodituwakku and Jens Gregor
Electronics 2025, 14(7), 1292; https://doi.org/10.3390/electronics14071292 - 25 Mar 2025
Cited by 2 | Viewed by 2371
Abstract
Endpoint Detection and Response (EDR) systems play a crucial role in continuously monitoring endpoint activities to detect, analyze, and respond to cybersecurity threats in real time. Traditional agent-based EDR systems rely on software agents installed on endpoints for data collection, which can be [...] Read more.
Endpoint Detection and Response (EDR) systems play a crucial role in continuously monitoring endpoint activities to detect, analyze, and respond to cybersecurity threats in real time. Traditional agent-based EDR systems rely on software agents installed on endpoints for data collection, which can be impractical due to the large number of devices, their mobility, and privacy concerns. In contrast, agentless EDR systems aim to overcome these limitations by remotely collecting network and host data, but they face challenges in precise data attribution because of the transient nature of network addresses. Achieving a fully zero-configuration agentless EDR system remains a significant challenge. This paper introduces InMesh, an innovative system that can identify and monitor endpoints without relying on network addressing or software agents. The effectiveness of the approach is demonstrated using real-world data. Full article
(This article belongs to the Special Issue Security and Privacy in Networks and Multimedia, 2nd Edition)
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18 pages, 3118 KB  
Article
A Methodology for Online Situational Awareness Provision in a Business Entity
by Marek Amanowicz
Electronics 2025, 14(3), 470; https://doi.org/10.3390/electronics14030470 - 24 Jan 2025
Viewed by 1241
Abstract
This paper presents a practical approach to building situational awareness at a critical infrastructure entity and its implementation in supporting security management. It outlines the main factors for achieving a high level of situational awareness and ensuring the safety and continuity of business [...] Read more.
This paper presents a practical approach to building situational awareness at a critical infrastructure entity and its implementation in supporting security management. It outlines the main factors for achieving a high level of situational awareness and ensuring the safety and continuity of business objectives. Among other things, situational awareness requires precise identification and understanding of multilateral dependencies of infrastructure, services, and processes executed by the entity and services provided by external businesses, resulting from the strong interrelationship of the critical infrastructure sectors and the sharing of resources. Accordingly, this paper presents a cyberspace modeling methodology that supports an in-depth analysis of the causes and consequences of threat proliferation in a complex infrastructure–business environment and its implementation in a Situational Awareness Management System (SAMS). An emphasis is placed on threat propagation analysis and dynamic risk assessment mechanisms and how they are used to identify and take preemptive actions protecting or limiting the scope of the threats’ propagation. The paper concludes with insights from a pilot implementation of the system prototype and directions for further work. Full article
(This article belongs to the Special Issue Security and Privacy in Networks and Multimedia, 2nd Edition)
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23 pages, 4260 KB  
Article
Robustness Against Data Integrity Attacks in Decentralized Federated Load Forecasting
by Attia Shabbir, Habib Ullah Manzoor, Muhmmand Naisr Manzoor, Sajjad Hussain and Ahmed Zoha
Electronics 2024, 13(23), 4803; https://doi.org/10.3390/electronics13234803 - 5 Dec 2024
Cited by 6 | Viewed by 1904
Abstract
This study examines the impact of data integrity attacks on Federated Learning (FL) for load forecasting in smart grid systems, where privacy-sensitive data require robust management. While FL provides a privacy-preserving approach to distributed model training, it remains susceptible to attacks like data [...] Read more.
This study examines the impact of data integrity attacks on Federated Learning (FL) for load forecasting in smart grid systems, where privacy-sensitive data require robust management. While FL provides a privacy-preserving approach to distributed model training, it remains susceptible to attacks like data poisoning, which can impair model performance. We compare Centralized Federated Learning (CFL) and Decentralized Federated Learning (DFL), using line, ring and bus topologies, under adversarial conditions. Employing a three-layer Artificial Neural Network (ANN) with substation-level datasets (APEhourly,PJMEhourly, and COMEDhourly), we evaluate the system’s resilience in the absence of anomaly detection. Results indicate that DFL significantly outperforms CFL in attack resistance, achieving Mean Absolute Percentage Errors (MAPEs) of 0.48%, 4.29% and 0.702% across datasets, compared to the CFL MAPEs of 6.07%, 18.49% and 10.19%. This demonstrates the potential of DFL as a resilient, secure solution for load forecasting in smart grids, minimizing dependence on anomaly detection to maintain data integrity. Full article
(This article belongs to the Special Issue Security and Privacy in Networks and Multimedia, 2nd Edition)
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Review

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51 pages, 2801 KB  
Review
A Review on Federated Learning Architectures for Privacy-Preserving AI: Lightweight and Secure Cloud–Edge–End Collaboration
by Shanhao Zhan, Lianfen Huang, Gaoyu Luo, Shaolong Zheng, Zhibin Gao and Han-Chieh Chao
Electronics 2025, 14(13), 2512; https://doi.org/10.3390/electronics14132512 - 20 Jun 2025
Cited by 43 | Viewed by 17395
Abstract
Federated learning (FL) has emerged as a promising paradigm for enabling collaborative training of machine learning models while preserving data privacy. However, the massive heterogeneity of data and devices, communication constraints, and security threats pose significant challenges to its practical implementation. This paper [...] Read more.
Federated learning (FL) has emerged as a promising paradigm for enabling collaborative training of machine learning models while preserving data privacy. However, the massive heterogeneity of data and devices, communication constraints, and security threats pose significant challenges to its practical implementation. This paper provides a system review of the state-of-the-art techniques and future research directions in FL, with a focus on addressing these challenges in resource-constrained environments by a cloud–edge–end collaboration FL architecture. We first introduce the foundations of cloud–edge–end collaboration and FL. We then discuss the key technical challenges. Next, we delve into the pillars of trustworthy AI in the federated context, covering robustness, fairness, and explainability. We propose a dimension reconstruction of trusted AI and analyze the foundations of each trustworthiness pillar. Furthermore, we present a lightweight FL framework for resource-constrained edge–end devices, analyzing the core contradictions and proposing optimization paradigms. Finally, we highlight advanced topics and future research directions to provide valuable insights into the field. Full article
(This article belongs to the Special Issue Security and Privacy in Networks and Multimedia, 2nd Edition)
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