Special Issue "Security and Privacy of Big Data: Issues, Challenges, and Future Perspectives"
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 10 August 2023 | Viewed by 1129
Special Issue Editor
Interests: cyber security; artificial intelligence; deep learning; big data
Special Issue Information
The gathering, processing, and analysis of the many types of organizational data have become more convenient and widespread as a result of the ongoing development of emerging technologies such as safe organizational systems, social networks, online commerce, and 5G systems. Because of this, personal information is frequently made more prone to being misused; consequently, it is becoming increasingly vital to investigate secure processes and optimized solutions for changing technologies.
The internet generates an incredible quantity of data, and the capacity to electronically store, transfer, and process that data is continuing to skyrocket along with the development of new technologies related to the internet. Big Data is a relatively new technology that has emerged in recent years as a response to this issue. Data security and privacy issues become more difficult to solve in the numerous processes that are involved due to the huge volume of data, including data collecting, storage, processing, and analysis. The general public, organizations, regulators, and data service providers all have a vested interest in, and a need for, cutting-edge technology and applications for maintaining the confidentiality and security of their customers' data.
This Special Issue, which strives to encourage high-quality submissions from the community, will focus on the preservation of data security and privacy in the context of Big Data processing as one of its areas of focus. We encourage contributions from a wide array of industries and types of data, such as business, finance, health, and mobility, because the issues and solutions around privacy protection are complicated and always changing (e.g., IoT, blockchain, social media, and networks).
Dr. Theyazn H.H. Aldhyani
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. Applied Sciences 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 2300 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.
- big data privacy and ethics
- differential privacy
- artificial intelligence on cybersecurity
- federated analytics
- privacy-preserving databases
- privacy-preserving analytics
- secure outsourcing
- trustworthy machine learning
- zero-trust architecture for data security
- intrusion detection system