posted by organizer: spathan || 995 views || tracked by 3 users: [display]

SI_DependXAIdata 2024 : SI on Dependable and Reliable Datasets for Explainable Artificial Intelligence and Cyber Security Research

FacebookTwitterLinkedInGoogle

Link: https://link.springer.com/collections/ccccjigagi
 
When N/A
Where N/A
Submission Deadline Jan 26, 2024
Notification Due Apr 26, 2024
Categories    dependable   reliable   explainable ai   cyber
 

Call For Papers

[CALL FOR PAPERS]

Topical Collection on
"Dependable and Reliable Datasets for Explainable Artificial Intelligence and Cyber Security Research"
Journal: Discover Data, Springer

URL: https://link.springer.com/collections/ccccjigagi

Submission deadline:
26 January 2024

There has been a severe need for publicly available benchmark datasets in the past decades for advancing artificial intelligence and cyber security research. Even in late 2000, researchers heavily used datasets developed by DARPA, such as DARPA 1998 and KDD Cup 1999. Researchers have identified the need for more recent and contemporary datasets representing different critical infrastructures and state-of-the-art cyber-attacks in the last few years. Still, there need to be more datasets that can represent the entire Internet-of-Everything ecosystem. Hence, there is an increasing demand for more current and publicly available datasets which can help develop explainable artificial intelligence-based solutions to address the newer variants of cyber-attacks.

This Topical Collection encourages researchers and industry practitioners to share their research and investigation on heterogenous cybercrime and associated datasets.

Topics include, but are not limited, to the following:

- Cyber Smart City
- Internet of Health Things
- Internet of Flying Things
- Internet of Family Things
- Smart Utilities
- Smart Airport
- Smart Home
- Cyber Physical Systems
- Operational Technology
- Unmanned Vehicles
- Autonomous Systems
- Wearable Devices
- Good Data
- Dark Data
- Under water Applications
- Covert Communications
- Surveillance
- Misinformation
- Deepfakes
- Ransomware
- Cryptocurrency
- Blockchain

Topic Editors

Mohiuddin Ahmed, Edith Cowan University, Australia; m.ahmed.au@ieee.org
Al-Sakib Khan Pathan, United International University, Bangladesh; spathan@ieee.org

To submit your papers, kindly go to this link and follow the instructions: https://link.springer.com/collections/ccccjigagi

===========================================

Regards,
Sakib
Guest Editor

--
Al-Sakib Khan Pathan, Ph.D., SMIEEE
Editor-in-Chief: International Journal of Computers and Applications, Taylor & Francis, UK
Editor-in-Chief: Journal of Cyber Security Technology, Taylor & Francis, UK
Associate Editor: Connection Science, Taylor & Francis, UK ; IJCSE, Inderscience
Editor: AHSWN, Old City Publishing, USA ; IJSNet, Inderscience ; MJCS
All My Books: https://sites.google.com/site/spathansite/books

Professor, Department of Computer Science and Engineering
United International University (UIU), Dhaka, Bangladesh
Email: sakib.pathan@gmail.com , spathan@ieee.org
URL: https://sites.google.com/site/spathansite/

Related Resources

SBD Summer School 2024   SoBigData RI Summer School 2024 Empowering data for social good
CXAI SI 2024   Special Issue on Causal and Explainable AI
AI-DCS 2024   The 1st IEEE International Workshop on Generative, Incremental, Adversarial, Explainable AI/ML in Distributed Computing Systems
IEEE-JBHI (SI) 2024   Special Issue on Revolutionizing Healthcare Informatics with Generative AI: Innovations and Implications
AI4SS Summer School 2024   Summer School on Artificial Intelligence for a Secure Society
xAI 2024   The 2nd World Conference on eXplainable Artificial Intelligence
CPAIOR 2024   International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research
EAIH 2024   Explainable AI for Health
DSN 2024   The 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks
WCCI-IJCNN SS 2024   Special Session on Applied AI for Reliable and Trustworthy Medical Decision-Making Systems