Guest Editors
Prof. Wen-Chen Hu
Email: wen.chen.hu@und.edu
Affiliation: School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks 58202, United States
Homepage:
Research Interests: Handheld/Mobile/Smartphone/Spatial Computing, Location-Based Services, Web-Enabled Information System, Electronic and Mobile Commerce Systems, Web Technologies
Dr. Sanjaikanth E Vadakkethil Somanathan Pillai
Email: s.evadakkethil@und.edu
Affiliation: School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks 58202, United States
Homepage:
Research Interests: Artificial Intelligence, Machine Learning, Security,Privacy, Mobile Networks
Prof. Piyush Kumar Pareek
Email: piyush.kumar@nmit.ac.in
Affiliation: Professor and Head (IPR Cell), Nitte Meenakshi Institute of Technology, Bengaluru, India
Homepage:
Research Interests: Software Engineering, Data Science, Data Compression, Image Processing, Deep Learning
Summary
1) Issue Introduction: Background and Importance
As AI technologies increasingly impact critical areas like healthcare, finance, and defense, the need for safe and secure AI systems is more important than ever. These systems bring powerful benefits but also introduce significant risks, including data privacy breaches, adversarial attacks, and algorithmic biases. Such challenges threaten both individual users and society as a whole, raising concerns about the reliability and ethical alignment of AI technologies. Addressing these issues is essential to ensure that AI systems are not only innovative but also robust, transparent, and trustworthy.
2) Aim and Scope of the Special Issue
This special issue aims to bring together interdisciplinary research and reviews that address the core challenges of AI safety and security. We seek to foster a multidisciplinary conversation on both theoretical and practical aspects, covering emerging risks, best practices, and technological innovations that enhance the reliability of AI systems. Contributions from computer science, engineering and ethics are encouraged, and topics may range from novel algorithms to case studies and empirical research. This issue is open to submissions that explore both technical solutions and broader implications for society, emphasizing research that contributes to a safer, more secure AI landscape.
3) Suggested Themes
-Trustworthy and Explainable AI
-Adversarial Machine Learning
-Data Privacy and Security
-Ethics and Governance of AI
-AI in Critical Infrastructure
-Bias and Fairness in AI
-AI Robustness and Reliability
-Secure Federated Learning
-AI and Cybersecurity
-Human-in-the-Loop AI
Keywords
Artificial Intelligence, Machine Learning, Security, Privacy, Fraud Detection, Secure Communication
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