Digital Privacy and Security, 3rd Edition

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Security and Privacy".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 2252

Special Issue Editors


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Guest Editor
COPELABS—Cognitive and People-Centric Computing, Lusófona University, 400098 Porto, Portugal
Interests: computer science; artificial intelligence; data science; knowledge management

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Guest Editor Assistant
COPELABS—Cognitive and People-Centric Computing, Lusófona University, 400098 Porto, Portugal
Interests: computer science; databases; system control; data mining; decision support systems

E-Mail Website
Guest Editor Assistant
COPELABS—Cognitive and People-Centric Computing, Lusófona University, 400098 Porto, Portugal
Interests: network security; cyibersecurity; serious games; player adaptivity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This is the 3rd edition of the Special Issue “Digital Privacy and Security”. The main objectives with regard to security, privacy, hacking, and cyber warfare are as follows: encouraging study, improving practice, and advancing knowledge; providing intended audiences with technological advancements; transferring knowledge; and encouraging applied research. The Special Issue brings together academic and industrial researchers from all areas of digital privacy and security to share their ideas as well as experiences and learn about the research in contemporary cybersecurity.

Dr. Jose de Vasconcelos
Guest Editor

Prof. Carla Cordeiro
Dr. Hugo Barbosa
Guest Editor Assistants

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. Information is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • authorization, authentication and identity management
  • cloud computing security
  • computer forensics
  • cybercrime
  • cyber security
  • cyber warfare
  • cryptography
  • cryptanalysis
  • data mining security
  • database security
  • data encryption applications
  • digital contents copyright protection
  • electronic mail security
  • emerging technologies and applications
  • formal methods application in security and forensics
  • forensic analysis
  • games for cybersecurity training and awareness
  • hacking techniques
  • information security management
  • management in network equipment
  • mobile network security
  • multimedia content management
  • network security management
  • policy of trust in E-leaning system
  • privacy and trust
  • security algorithms
  • security in E-commerce and M-commerce
  • security in contents distribution networks
  • security protocols
  • system security management
  • social networks & web 2.0 trust management
  • storage area networks management
  • tracing techniques in internet
  • wired and wireless network security and investigation

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Published Papers (3 papers)

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Research

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32 pages, 716 KB  
Article
UDPLDP-Tree: Range Queries Under User-Distinguished Personalized Local Differential Privacy
by Dongli Deng, Sen Zhao and Meixia Miao
Information 2026, 17(2), 181; https://doi.org/10.3390/info17020181 - 10 Feb 2026
Viewed by 326
Abstract
Local Differential Privacy (LDP) and its personalized variants (PLDP) have been widely used for privacy-preserving data analytics. However, existing schemes often enforce a uniform indistinguishability level among users, failing to accommodate the nuanced privacy needs of diverse individuals. To address this, we propose [...] Read more.
Local Differential Privacy (LDP) and its personalized variants (PLDP) have been widely used for privacy-preserving data analytics. However, existing schemes often enforce a uniform indistinguishability level among users, failing to accommodate the nuanced privacy needs of diverse individuals. To address this, we propose User-Distinguished Local Differential Privacy (UDPLDP), a novel framework that formalizes user-level distinguishability to support more flexible, non-uniform privacy budgets. Under this framework, we tackle the fundamental task of frequency range queries, namely UDPLDP-Tree, which overcomes the challenge due to limited user-level distinguishability, insufficient robustness in estimation under complex data distributions, and the assumption of uniform privacy requirements across different attributes in existing multi-dimensional schemes. To demonstrate the effectiveness, we conduct extensive experiments and the results show that UDPLDP-Tree reduces the mean squared error (MSE) by about 30–50% compared with a recent state-of-the-art baseline. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 3rd Edition)
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Review

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22 pages, 1040 KB  
Review
Cybersecurity Challenges of Digital Transformation in the Entertainment Industry
by Manar Saleh Husain, Shroog Abdulhadi M. Alqahtani, Saqib Saeed, Hina Gull, Sardar Zafar Iqbal and Madeeha Saqib
Information 2026, 17(3), 219; https://doi.org/10.3390/info17030219 - 25 Feb 2026
Viewed by 749
Abstract
Digital transformation has transformed human work practices, organizational processes, and the way of entertainment. Such transformations have resulted in improvements in entertainment content quality, personalized delivery of content and faster production cycles. However, cybersecurity threats and vulnerabilities have also increased and require agile [...] Read more.
Digital transformation has transformed human work practices, organizational processes, and the way of entertainment. Such transformations have resulted in improvements in entertainment content quality, personalized delivery of content and faster production cycles. However, cybersecurity threats and vulnerabilities have also increased and require agile cybersecurity processes and tools. In this paper, we have carried out a literature review to understand cybersecurity implications in the digital transformation of the entertainment sector. We have found that many studies have explored the cybersecurity challenges in sports, gaming, live streaming, games, and gambling domains; however, there is a need for more systematic studies to further strengthen this body of knowledge. We have presented a taxonomy of related themes as well as challenges faced to enhance the cybersecurity practices in this sector. The findings will provide an interesting research agenda for researchers and practitioners to explore this sector as well. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 3rd Edition)
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Other

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43 pages, 6661 KB  
Systematic Review
Privacy and Security in Health Big Data: A NIST-Guided Systematic Review of Technologies, Challenges, and Future Directions
by Siyuan Zhang and Manmeet Mahinderjit Singh
Information 2026, 17(2), 148; https://doi.org/10.3390/info17020148 - 2 Feb 2026
Viewed by 843
Abstract
The rapid expansion of health big data, encompassing genomic profiles and wearable device telemetry, has significantly escalated personal privacy risks. This systematic literature review (SLR) synthesizes 86 peer-reviewed studies (2014–2025) through the dual lens of the NIST Cybersecurity and Privacy Frameworks to evaluate [...] Read more.
The rapid expansion of health big data, encompassing genomic profiles and wearable device telemetry, has significantly escalated personal privacy risks. This systematic literature review (SLR) synthesizes 86 peer-reviewed studies (2014–2025) through the dual lens of the NIST Cybersecurity and Privacy Frameworks to evaluate emerging risks, mitigation technologies, and regulatory landscapes. Our analysis identifies unauthorized access as the predominant threat, while blockchain-based solutions comprise 22.1% of proposed interventions. However, a comparative evaluation reveals critical performance trade-offs: differential privacy mechanisms incur a 15–35% utility loss, whereas blockchain implementations impose a 40–50% computational overhead. Furthermore, an assessment of major regulatory frameworks (GDPR, HIPAA, PIPL, and emerging regional laws in Sub-Saharan Africa) elucidates significant cross-jurisdictional conflicts. To address these challenges, we propose the Bio-inspired Adaptive Healthcare Privacy (BAHP) framework, validated through retrospective case study analysis, offering a dynamic approach to securing sensitive health ecosystems. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 3rd Edition)
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