Submission Deadline: 01 November 2025 View: 116 Submit to Special Issue
Dr. Rahim Taheri
Email: rahim.taheri@port.ac.uk
Affiliation: School of Computing, University of Portsmouth, Portsmouth, PO1 3HE, United Kingdom
Research Interests: differential privacy, federated learning, adversarial machine learning
Dr. Yousef Emami
Email: emami@isep.ipp.pt
Affiliation: CISTR, Research Center in Real-Time & Embedded Computing Systems, 4249-015, University of Porto, 4099-002 Porto, Portugal
Research Interests: security and privacy, machine learning, decision-making and modeling
Dr. Ahmad Hassanpour
Email: ahmad.hassanpour@ntnu.no
Affiliation: Department of Information Security and Communication Technology, Norwegian University of Science and Technology, NO-2815 Gjøvik, Norway
Research Interests: differential privacy, machine learning, computer vision
Differential Privacy (DP) is a new approach in data privacy that helps share information safely while protecting individual privacy. With the increase of technology use in areas like healthcare, finance, and public services, ensuring the security of personal data has become crucial, both for ethical and legal reasons. Differential privacy provides strong protections and is key in research and practical applications, helping balance the usefulness of data with privacy needs.
This special issue aims to explore innovative differential privacy techniques, address the challenges in practical implementations, and showcase applications across various fields where DP can offer significant benefits. It will focus on novel techniques for implementing DP, understanding the theoretical underpinnings, addressing scalability and efficiency challenges, and exploring real-world applications. The issue will also examine the balance between data utility and privacy assurance, aiming to push forward the boundaries of what can be achieved with DP.
The following subtopics are the particular interests of this special issue, including but not limited to:
· Advanced Techniques in Differential Privacy
· Challenges in Differential Privacy
· Applications of Differential Privacy
· Theoretical Foundations of Differential Privacy
· Regulatory and Ethical Considerations
· Technology and Infrastructure
· Impact of Differential Privacy on AI and Machine Learning
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