Advances in Data Security: Challenges, Technologies, and Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 December 2025 | Viewed by 321
Special Issue Editors
Interests: data mining; natural language processing; graph neural network
Special Issues, Collections and Topics in MDPI journals
Interests: data mining; data privacy; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In today's data-driven world, the exponential growth of digital information and the rapid adoption of emerging technologies such as cloud computing, the Internet of Things (IoT), and artificial intelligence have brought unprecedented opportunities—and significant security challenges. Ensuring data security has become a critical concern for researchers, practitioners, and policymakers across a wide range of domains, from finance and healthcare to government and industrial systems.
This Special Issue aims to provide a comprehensive forum for the latest research and developments in data security. We invite original contributions that address fundamental challenges, propose innovative technologies, or demonstrate practical applications for securing data across diverse platforms and environments. Topics of interest include, but are not limited to, the following:
- Data encryption and secure computation;
- Privacy-preserving machine learning;
- Blockchain and distributed ledger technologies for data security;
- Intrusion detection and anomaly detection in large-scale systems;
- Secure data sharing and access control;
- Security in edge and cloud computing environments;
- Cyber–physical systems and IoT data protection;
- Formal methods and verification for data security;
- Adversarial attacks and defenses in data-driven models;
- Real-world case studies and applications in critical sectors.
By bringing together interdisciplinary perspectives, this Special Issue seeks to foster a deeper understanding of data security challenges and promote the development of robust, scalable, and practical security solutions for the future.
Dr. Lanting Fang
Dr. Yubo Song
Guest Editors
Manuscript Submission Information
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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
- data mining
- data encryption
- machine learning
- data security
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