Symmetry Applied in Privacy and Security for Big Data Analytics
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 6629
Special Issue Editor
Interests: big data privacy and security; artificial intelligence security; IoT security and computing; online learning; deep learning; industrail IOT; computer vision and its security; wireless network security, reinforcement learning and other cutting-edge artificial intelligence design and privacy protection
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleague,
With the rapid development of information and communication technologies (ICTs; e.g., 5G, mobile edge computing, smart mobile edge devices, and social networks), the generated massive big datasets lead to an exceptional increase in research activities in big data. At present, many big data analytics tasks request the reform of mobile users’ personal data protection legal framework in the context of the adoption of a General Data Protection Regulation (GDPR), which exhibits the importance of privacy and security issues in big data research. Big data security has become an indispensable requirement in our lives—not only for personal privacy, but also for exploring and the potential symmetry to assure analytics efficiency and security performance. Advanced associated technologies central to and at the periphery of this research domain include blockchain, mobile cloud/edge computing, artificial intelligence, social networks, smart healthcare, smart city, Industry 4.0, etc. For example, blockchain has the capability to enhance predictive analytics because it verifies data validity, preventing false information with trustness from being included in big data analyses. The big data security market was valued at USD 17.38 billion in 2019, and is projected to reach USD 57.29 billion by 2027, growing at a CAGR of 17.35% from 2020 to 2027. This Special Issue aims to present cutting-edge research addressing privacy and security protection challenges in big data analytics. Original and unpublished high-quality research results are solicited to explore various challenging topics which include, but are not limited to:
- The intersection of blockchain and the symmetry applied in privacy and security issues of big data analytics;
- Symmetry applied in the privacy and security of personal health records big data;
- Security/privacy/trust and symmetry applied in big data issues in mobile cloud/edge computing;
- Security/privacy/trust and symmetry applied in big data issues in social networks, smart healthcare, smart cities, Industry 4.0, etc.;
- Security/privacy/trust-enabled big data mining methods for symmetry applied in big data analytics;
- Adversarial attack and defense in symmetry-applied AI-enabled big data systems;
- Symmetry applied in case study experience reports on big data security, privacy, and trust;
- Symmetry applied in private information retrieval over typical big data platforms;
- Symmetry applied in data-centric security and data classification;
- Symmetry applied in cost and usability models related security issues in mobile and social network big data;
- Symmetry applied in privacy-preserving machine-learning methods for big data analytics;
- Symmetry applied in security and privacy policies for big data analytics;
- Symmetry applied in secure big data management.
Prof. Dr. Pan Zhou
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. Symmetry 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 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
- big data analytics
- privacy and security for big data
- blockchain
- social networks
- health records
- mobile cloud
- smart cities
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 policies can be found here.