Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.9
2.4
Journals
Information
Special Issues
Digital Privacy and Security, 2nd Edition
share announcement

Digital Privacy and Security, 2nd 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 December 2024 | Viewed by 6809

Special Issue Editors

Dr. José Braga de Vasconcelos

E-Mail Website
Guest Editor
COPELABS—Cognitive and People-Centric Computing, Lusófona University, 400098 Porto, Portugal
Interests: computer science; artificial intelligence; data science; knowledge management
Special Issues, Collections and Topics in MDPI journals
Dr. Hugo Barbosa

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

E-Mail Website
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
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the 2nd edition of 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 conference 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

Dr. Hugo Barbosa
Dr. Carla Cordeiro
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 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. Information 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 1600 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

  • 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 content copyright protection
  • electronic mail security
  • emerging technologies and applications
  • formal method 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
  • policies of trust in e-learning systems
  • privacy and trust
  • security algorithms
  • security in e-commerce and m-commerce
  • security in content distribution networks
  • security protocols
  • system security management
  • social networks and web 2.0 trust management
  • storage area networks management
  • tracing techniques on the internet
  • wired and wireless network security and investigation

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review, Other

16 pages, 1480 KiB  
Article
Protecting Infinite Data Streams from Wearable Devices with Local Differential Privacy Techniques
by Feng Zhao and Song Fan
Information 2024, 15(10), 630; https://doi.org/10.3390/info15100630 - 12 Oct 2024
Viewed by 563
Abstract
The real-time data collected by wearable devices enables personalized health management and supports public health monitoring. However, sharing these data with third-party organizations introduces significant privacy risks. As a result, protecting and securely sharing wearable device data has become a critical concern. This [...] Read more.
The real-time data collected by wearable devices enables personalized health management and supports public health monitoring. However, sharing these data with third-party organizations introduces significant privacy risks. As a result, protecting and securely sharing wearable device data has become a critical concern. This paper proposes a local differential privacy-preserving algorithm designed for continuous data streams generated by wearable devices. Initially, the data stream is sampled at key points to avoid prematurely exhausting the privacy budget. Then, an adaptive allocation of the privacy budget at these points enhances privacy protection for sensitive data. Additionally, the optimized square wave (SW) mechanism introduces perturbations to the sampled points. Afterward, the Kalman filter algorithm is applied to maintain data flow patterns and reduce prediction errors. Experimental validation using two real datasets demonstrates that, under comparable conditions, this approach provides higher data availability than existing privacy protection methods for continuous data streams. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 2nd Edition)
►▼ Show Figures

Graphical abstract

17 pages, 560 KiB  
Article
Smartphone Privacy and Cyber Safety among Australian Adolescents: Gender Differences
by Yeslam Al-Saggaf and Julie Maclean
Information 2024, 15(10), 604; https://doi.org/10.3390/info15100604 - 2 Oct 2024
Viewed by 684
Abstract
While existing studies explore smartphone privacy setting risks for adolescents, they provide limited insight into the role of gender in these dynamics. This study aims to enhance adolescents’ awareness of the security risks associated with smartphone privacy leakage by focusing on how a [...] Read more.
While existing studies explore smartphone privacy setting risks for adolescents, they provide limited insight into the role of gender in these dynamics. This study aims to enhance adolescents’ awareness of the security risks associated with smartphone privacy leakage by focusing on how a cyber safety intervention lesson can affect knowledge of smartphone privacy settings, attitudes toward smartphone settings, and concerns about smartphone privacy. This study surveyed 376 high school students before and after a cyber safety lesson. Our study found that before the cyber safety intervention, females reported lower knowledge of smartphone settings than males. After the lesson, this gap narrowed, with both genders demonstrating more consistent understanding. Both genders showed lower attitudes towards smartphone privacy compared to knowledge, with males displaying the largest gap, reflecting the privacy paradox. Females expressed greater concern regarding location privacy, especially when tracked by unknown individuals, indicating that while both genders are aware of risks, females perceive them more acutely. The results suggest that targeted educational programs can effectively enhance adolescents’ knowledge, attitudes, and concerns about smartphone privacy, particularly in technical areas where gender gaps exist. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 2nd Edition)
►▼ Show Figures

Figure 1

31 pages, 4888 KiB  
Article
Efficient Cryptographic Solutions for Unbalanced Private Set Intersection in Mobile Communication
by Qian Feng, Shenglong Du, Wuzheng Tan and Jian Weng
Information 2024, 15(9), 554; https://doi.org/10.3390/info15090554 - 9 Sep 2024
Viewed by 686
Abstract
Private Set Intersection (PSI) is a cryptographic method in secure multi-party computation that allows entities to identify common elements in their datasets without revealing their private data. Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances. In real-world applications, dataset [...] Read more.
Private Set Intersection (PSI) is a cryptographic method in secure multi-party computation that allows entities to identify common elements in their datasets without revealing their private data. Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances. In real-world applications, dataset sizes and computational capacities often vary, particularly in the Internet of Things and mobile scenarios where device limitations restrict computational types. Traditional PSI protocols are inefficient here, as computational and communication complexities correlate with the size of larger datasets. Thus, adapting PSI protocols to these imbalances is crucial. This paper explores unbalanced PSI scenarios where one party (the receiver) has a relatively small dataset and limited computational power, while the other party (the sender) has a large amount of data and strong computational capabilities. It introduces three innovative solutions for unbalanced PSI: an unbalanced PSI protocol based on the Cuckoo filter, an unbalanced PSI protocol based on single-cloud assistance, and an unbalanced PSI protocol based on dual-cloud assistance, with each subsequent solution addressing the shortcomings of the previous one. Depending on performance and security needs, different protocols can be employed for applications such as private contact discovery. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 2nd Edition)
►▼ Show Figures

Figure 1

17 pages, 1231 KiB  
Article
Privacy and Security Mechanisms for B2B Data Sharing: A Conceptual Framework
by Wanying Li, Woon Kwan Tse and Jiaqi Chen
Information 2024, 15(6), 308; https://doi.org/10.3390/info15060308 - 26 May 2024
Viewed by 1726
Abstract
In the age of digitalization, business-to-business (B2B) data sharing is becoming increasingly important, enabling organizations to collaborate and make informed decisions as well as simplifying operations and hopefully creating a cost-effective virtual value chain. This is crucial to the success of modern businesses, [...] Read more.
In the age of digitalization, business-to-business (B2B) data sharing is becoming increasingly important, enabling organizations to collaborate and make informed decisions as well as simplifying operations and hopefully creating a cost-effective virtual value chain. This is crucial to the success of modern businesses, especially global business. However, this approach also comes with significant privacy and security challenges, thus requiring robust mechanisms to protect sensitive information. After analyzing the evolving status of B2B data sharing, the purpose of this study is to provide insights into the design of theoretical framework solutions for the field. This study adopts technologies including encryption, access control, data anonymization, and audit trails, with the common goal of striking a balance between facilitating data sharing and protecting data confidentiality as well as data integrity. In addition, emerging technologies such as homomorphic encryption, blockchain, and their applicability as well as advantages in the B2B data sharing environment are explored. The results of this study offer a new approach to managing complex data sharing between organizations, providing a strategic mix of traditional and innovative solutions to promote secure and efficient digital collaboration. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 2nd Edition)
►▼ Show Figures

Figure 1

Review

Jump to: Research, Other

19 pages, 6680 KiB  
Review
Reliablity and Security for Fog Computing Systems
by Egor Shiriaev, Tatiana Ermakova, Ekaterina Bezuglova, Maria A. Lapina and Mikhail Babenko
Information 2024, 15(6), 317; https://doi.org/10.3390/info15060317 - 29 May 2024
Viewed by 911
Abstract
Fog computing (FC) is a distributed architecture in which computing resources and services are placed on edge devices closer to data sources. This enables more efficient data processing, shorter latency times, and better performance. Fog computing was shown to be a promising solution [...] Read more.
Fog computing (FC) is a distributed architecture in which computing resources and services are placed on edge devices closer to data sources. This enables more efficient data processing, shorter latency times, and better performance. Fog computing was shown to be a promising solution for addressing the new computing requirements. However, there are still many challenges to overcome to utilize this new computing paradigm, in particular, reliability and security. Following this need, a systematic literature review was conducted to create a list of requirements. As a result, the following four key requirements were formulated: (1) low latency and response times; (2) scalability and resource management; (3) fault tolerance and redundancy; and (4) privacy and security. Low delay and response can be achieved through edge caching, edge real-time analyses and decision making, and mobile edge computing. Scalability and resource management can be enabled by edge federation, virtualization and containerization, and edge resource discovery and orchestration. Fault tolerance and redundancy can be enabled by backup and recovery mechanisms, data replication strategies, and disaster recovery plans, with a residual number system (RNS) being a promising solution. Data security and data privacy are manifested in strong authentication and authorization mechanisms, access control and authorization management, with fully homomorphic encryption (FHE) and the secret sharing system (SSS) being of particular interest. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 2nd Edition)
►▼ Show Figures

Figure 1

Other

Jump to: Research, Review

19 pages, 3593 KiB  
Perspective
Improving the Cybersecurity Awareness of Young Adults through a Game-Based Informal Learning Strategy
by Giorgia Tempestini, Sara Merà, Marco Pietro Palange, Alexandra Bucciarelli and Francesco Di Nocera
Information 2024, 15(10), 607; https://doi.org/10.3390/info15100607 - 3 Oct 2024
Viewed by 1526
Abstract
Knowing about a danger is not enough to avoid it. Our daily lives offer countless examples of occasions in which we act imprudently for various reasons, even though we know we are taking risks. Nevertheless, circumstances in which we lack the necessary knowledge [...] Read more.
Knowing about a danger is not enough to avoid it. Our daily lives offer countless examples of occasions in which we act imprudently for various reasons, even though we know we are taking risks. Nevertheless, circumstances in which we lack the necessary knowledge can lead us to run into unpleasant or harmful situations without being aware of it. In cybersecurity, knowledge of the dangers (as well as the mechanics of a possible attack) makes a huge difference. This is why specific training is provided in organizations, along with awareness campaigns. However, security training is often generic, boring, and a mere fulfillment of obligations rather than a tool for behavioral change. Today, we can deliver content through various devices and platforms that people access for both work and leisure, so that learning can happen incidentally and with almost no effort. Distributing knowledge in small, dedicated units creates the conditions for lasting, effective learning and is more effective than teaching through traditional courses (whether delivered in-person or online). In this article, we present an ongoing project on cybersecurity informal learning, including the design of a small video game. The intervention is aimed at helping young adults (18–25 years) to understand the mechanics of cookies and their role in the dynamics of cyberattacks. Consistent with the idea that a comprehensive course may be unsuitable for delivering cybersecurity training, the game covers and deliberately limits itself to that topic only. We also provide detailed considerations related to the evaluation of its effectiveness, although this is outside the scope of the present paper. Full article
(This article belongs to the Special Issue Digital Privacy and Security, 2nd Edition)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop