We are happy to present this special issue titled "Enhancing Decision-Making with Machine Learning and AI: Privacy-Preserving Access Control for Data Analysis and Applications", which brings together innovative research contributions at the intersection of artificial intelligence, machine learning, and data privacy.
In the digital era, the exponential growth of data has empowered organizations and researchers to make smarter, data-driven decisions. However, this progress comes with significant concerns surrounding privacy, security, and ethical data use. This special issue aims to address these concerns by exploring how intelligent techniques and privacy-preserving mechanisms can be integrated into decision-making systems and analytical models.
The articles featured in this issue cover a wide spectrum of topics, including but not limited to:
This curated collection represents the collaborative efforts of researchers, practitioners, and domain experts who are driving advancements in responsible AI and secure data analytics. We are confident that the contributions in this issue will serve as a valuable resource for academics, developers, and decision-makers seeking to build intelligent systems that balance utility with privacy.
We extend our sincere gratitude to all the authors for their high-quality submissions and to the reviewers for their timely and insightful feedback. We also thank the editorial team and the journal management for their continued support in bringing this special issue to fruition.
We hope that the research presented in this issue will inspire further exploration and innovation in building AI systems that are not only intelligent but also secure, ethical, and trustworthy.