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Research on Privacy and Data Security
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Research on Privacy and Data Security

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 3920

Special Issue Editor

Prof. Dr. Hui Tian

E-Mail Website
Guest Editor
College of Computer Science and Technology, National Huaqiao University, Xiamen 361021, China
Interests: network and information security; information hiding; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The pervasive digitalization of modern society has initiated unprecedented challenges and opportunities in the realm of privacy and data security. This Special Issue aims to gather cutting-edge research contributions that advance our understanding and address the multifaceted issues surrounding privacy and data security in various domains. We invite original research papers, case studies, and review articles that shed light on emerging trends, innovative solutions, and best practices in safeguarding privacy and enhancing data security in the digital age.

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

  • Privacy-preserving techniques in data collection, storage, and processing;
  • Data anonymization, encryption, and obfuscation methods;
  • Privacy-enhancing technologies (PETs) and their applications;
  • Threat modeling and risk assessment in data security;
  • Privacy and security issues in IoT, cloud computing, and edge computing;
  • Privacy policies, regulations, and compliance frameworks;
  • User-centric approaches to privacy protection and data security;
  • Ethical considerations in data handling and privacy preservation;
  • Blockchain and distributed ledger technologies for privacy and security;
  • Privacy and security implications of emerging technologies (e.g., AI and machine learning);
  • Steganography and steganalysis;
  • Digital watermarking and information hiding;
  • Digital forensics.

Submission Guidelines:

  • Manuscripts should be prepared according to the journal's formatting guidelines.
  • All submissions will undergo a rigorous peer-review process.
  • Manuscripts must be submitted electronically via the journal's online submission system.
  • Authors should clearly indicate that the submission is for consideration in the Special Issue on "Research on Privacy and Data Security".

Note: Submissions that offer novel insights, empirical findings, and practical implications for advancing privacy and data security research will be given priority. We encourage submissions from both academia and industry professionals.

Prof. Dr. Hui Tian
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. Big Data and Cognitive Computing 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 1800 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

  • privacy
  • data Security
  • data collection, storage, and processing
  • privacy-enhancing technologies
  • IoT
  • AI
  • machine Learning

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

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17 pages, 751 KiB  
Article
Usable Privacy and Security in Mobile Applications: Perception of Mobile End Users in Saudi Arabia
by Saqib Saeed
Big Data Cogn. Comput. 2024, 8(11), 162; https://doi.org/10.3390/bdcc8110162 - 18 Nov 2024
Viewed by 514
Abstract
Privacy and security is very critical for mobile users and in-depth research into the area highlights a need for more scientific literature on the perception and challenges of end users to better align the design of privacy and security controls with user expectations. [...] Read more.
Privacy and security is very critical for mobile users and in-depth research into the area highlights a need for more scientific literature on the perception and challenges of end users to better align the design of privacy and security controls with user expectations. In this paper, we have explored the perceptions of the usability of privacy and security settings in mobile applications from mobile users in Saudi Arabia. The findings highlight that gender, age, and education level of users do not have any positive correlation with the privacy and security usability perceptions of mobile users. On the other hand, user concerns about privacy and security and the trustworthiness levels of end users regarding mobile phone privacy and security have a positive impact on end users’ perception of privacy and security usability. Furthermore, privacy usability perception has a positive impact on users’ feelings about their control over the privacy and security of their mobile phones. Based on the results of this empirical study, we propose that user-centric design of privacy and security controls, transparent data handling policies, periodic data management status preview and validation by end users, user education guidelines, strict governmental policies, and automated security settings recommendations can enhance the usability of the privacy and security of mobile phone applications. Our study did not take the geographical location of respondents into account, nor were the respondents balanced based on age and gender. In future work, these weaknesses need to be taken into account, and more qualitative studies can help to extract design guidelines for usable and secure mobile applications. Full article
(This article belongs to the Special Issue Research on Privacy and Data Security)
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26 pages, 2545 KiB  
Article
An Inquiry into the Evolutionary Game among Tripartite Entities and Strategy Selection within the Framework of Personal Information Authorization
by Jie Tang, Zhiyi Peng and Wei Wei
Big Data Cogn. Comput. 2024, 8(8), 90; https://doi.org/10.3390/bdcc8080090 - 8 Aug 2024
Viewed by 741
Abstract
Mobile applications (Apps) serve as vital conduits for information exchange in the mobile internet era, yet they also engender significant cybersecurity risks due to their real-time handling of vast quantities of data. This manuscript constructs a tripartite evolutionary game model, “users-App providers-government”, to [...] Read more.
Mobile applications (Apps) serve as vital conduits for information exchange in the mobile internet era, yet they also engender significant cybersecurity risks due to their real-time handling of vast quantities of data. This manuscript constructs a tripartite evolutionary game model, “users-App providers-government”, to illuminate a pragmatic pathway for orderly information circulation within the App marketplace and sustainable industry development. It then scrutinizes the evolutionary process and emergence conditions of their stabilizing equilibrium strategies and employs simulation analysis via MATLAB. The findings reveal that (1) there exists a high degree of coupling among the strategic selections of the three parties, wherein any alteration in one actor’s decision-making trajectory exerts an impact on the evolutionary course of the remaining two actors. (2) The initial strategies significantly influence the pace of evolutionary progression and its outcome. Broadly speaking, the higher the initial probabilities of users opting for information authorization, App providers adopting compliant data solicitation practices, and the government enforcing stringent oversight, the more facile the attainment of an evolutionarily optimal solution. (3) The strategic preferences of the triadic stakeholders are subject to a composite influence of respective costs, benefits, and losses. Of these, users’ perceived benefits serve as the impetus for their strategic decisions, while privacy concerns act as a deterrent. App providers’ strategy decisions are influenced by a number of important elements, including their corporate reputation and fines levied by the government. Costs associated with government regulations are the main barrier to the adoption of strict supervision practices. Drawing upon these analytical outcomes, we posit several feasible strategies. Full article
(This article belongs to the Special Issue Research on Privacy and Data Security)
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28 pages, 2936 KiB  
Systematic Review
Medical IoT Record Security and Blockchain: Systematic Review of Milieu, Milestones, and Momentum
by Simeon Okechukwu Ajakwe, Igboanusi Ikechi Saviour, Vivian Ukamaka Ihekoronye, Odinachi U. Nwankwo, Mohamed Abubakar Dini, Izuazu Urslla Uchechi, Dong-Seong Kim and Jae Min Lee
Big Data Cogn. Comput. 2024, 8(9), 121; https://doi.org/10.3390/bdcc8090121 - 12 Sep 2024
Viewed by 2029
Abstract
The sensitivity and exclusivity attached to personal health records make such records a prime target for cyber intruders, as unauthorized access causes unfathomable repudiation and public defamation. In reality, most medical records are micro-managed by different healthcare providers, exposing them to various security [...] Read more.
The sensitivity and exclusivity attached to personal health records make such records a prime target for cyber intruders, as unauthorized access causes unfathomable repudiation and public defamation. In reality, most medical records are micro-managed by different healthcare providers, exposing them to various security issues, especially unauthorized third-party access. Over time, substantial progress has been made in preventing unauthorized access to this critical and highly classified information. This review investigated the mainstream security challenges associated with the transmissibility of medical records, the evolutionary security strategies for maintaining confidentiality, and the existential enablers of trustworthy and transparent authorization and authentication before data transmission can be carried out. The review adopted the PRSIMA-SPIDER methodology for a systematic review of 122 articles, comprising 9 surveys (7.37%) for qualitative analysis, 109 technical papers (89.34%), and 4 online reports (3.27%) for quantitative studies. The review outcome indicates that the sensitivity and confidentiality of a highly classified document, such as a medical record, demand unabridged authorization by the owner, unquestionable preservation by the host, untainted transparency in transmission, unbiased traceability, and ubiquitous security, which blockchain technology guarantees, although at the infancy stage. Therefore, developing blockchain-assisted frameworks for digital medical record preservation and addressing inherent technological hitches in blockchain will further accelerate transparent and trustworthy preservation, user authorization, and authentication of medical records before they are transmitted by the host for third-party access. Full article
(This article belongs to the Special Issue Research on Privacy and Data Security)
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