Secure and Efficient AI on the Edge
Co-organizers:
Riyadh Baghdadi, Ph.D.
New York University at Abu Dhabi, UAE
Karima Benatchba, Ph.D.
Professor
Ecole nationale Supérieure d’Informatique, Algeria
Yacine Challal, Ph.D.
Professor
University of Doha for Science and Technology, Qatar
yacine.challal (at) udst.edu.qa
Artificial Intelligence on the Edge (AIoEdge) promises cutting edge applications in industry automation, predictive maintenance, remote healthcare, precision agriculture, surveillance, and disaster recovery. It brings intelligence to the edge of the network allowing to tackle many issues related to data and AI models ownership. However, bringing intelligence to the edge raises many issues related to the efficiency and allocation of required resources to run heavy algorithms. Moreover, the integration of intelligent things into sensitive systems sharpens security requirements and may not alleviate all privacy concerns.
This workshop aims to shed some light on efficient and secure architectures and privacy-preserving machine learning solutions that fit operational constraints and requirements of artificial intelligence applications on the edge.
The Workshop is an opportunity for researchers to share knowledge and experiences with the broader community and to facilitate collaboration. The workshop seeks presentations of original works and/or previous experiences and works in progress aiming to foster discussions and reflections on the hot topic of secure AI on the Edge.
Topics of interest include but are not limited to:
- Security challenges in AIoEdge and AIoT
- Resource allocation in AIoEdge
- Performing machine learning algorithms on homomorphically encrypted data
- Federated learning and blockchain for AIoEdge
- Machine learning code optimization for heterogeneous platforms including hardware accelerators
- Secure and efficient AI in IoT over 5G/6G networks
- Elastic resource allocation in Cloud/Edge systems for AIoEdge
- Slice management for secure and efficient AIoEdge in 5G/6G networks
Submission guidelines:
Authors are invited to submit a 1-page abstract of their presentation. The Technical Program Committee will review proposals, make selections and inform each speaker of their decision to accept the inclusion of their presentation in the workshop program.
Workshop Important Dates:
Workshop Presentation Abstract Submission Deadline: September 30th 2024.
Presentation Acceptance Notification: October 15th 2024
Abstract submission:
Submit your abstract.
Select the workshop track on EDAS to submit your abstract to this workshop.
Registration:
Visit HONET registration page
here.