Security and Privacy in AI: Human Interaction, Awareness and Protection
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 6
Special Issue Editors
Interests: privacy protection; cyber security; homomorphic; blockchain; privacy in AI
Interests: machine learning; edge computing; blockchain
Interests: cybersecurity and privacy; artificial intelligence; data management and data science; distributed computing and systems software
Interests: data privacy; cloud security; cyber security; wireless and mobile security; applied cryptography
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the rapid advancement and widespread adoption of artificial intelligence (AI), ensuring the security and privacy of AI systems has become a critical concern—particularly in contexts where human interaction is deeply involved. As AI technologies permeate areas such as healthcare, education, finance, and public governance, they introduce not only unprecedented opportunities, but also new risks in terms of data exposure, adversarial manipulation, and erosion of user trust.
This Special Issue aims to explore cutting-edge developments in AI security and privacy from a human-centric perspective. We invite original research and review articles addressing technical solutions, human awareness strategies, policy frameworks, and ethical considerations related to AI deployment. Topics may include privacy-preserving learning models, human-in-the-loop defense mechanisms, explainable AI (XAI), and the societal impacts of automated decision-making. The goal is to build a more trustworthy AI landscape where protection of individual rights, transparency, and accountability are prioritized.
The scope includes, but is not limited to, the following topics:
- Securing AI systems from adversarial threats;
- Privacy-aware machine learning and data handling;
- Human-in-the-loop security approaches;
- Awareness and education on AI privacy risks;
- Explainability and interpretability in AI decision-making;
- Trust frameworks for human–AI interaction;
- Case studies on AI privacy and security in real-world use;
- Other original work in the intersection of security, privacy, AI, and humans.
Dr. Xuechao Yang
Dr. Chenhao Xu
Dr. Jack Li
Prof. Dr. Xun Yi
Guest Editors
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 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
- AI security
- data privacy
- adversarial attacks
- human-in-the-loop
- explainable AI
- trust in AI
- privacy awareness
- real-world AI cases
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