EarlyExodus: Leveraging early exits to mitigate backdoor vulnerability in deep learning
The rapid migration of artificial-intelligence workloads toward edge computing significantly enhances capabilities in critical applications such as autonomous vehicles, augmented and virtual reality, and e-health, but it also heightens the urgency for robust security. However, this urgency reveals a...
Saved in:
Main Authors: | Salmane Douch, M. Riduan Abid, Khalid Zine-Dine, Driss Bouzidi, Fatima Ezzahra El Aidos, Driss Benhaddou |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-09-01
|
Series: | Results in Engineering |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025024740 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Backdoor Approach With Inverted Labels Using Dirty Label-Flipping Attacks
by: Orson Mengara
Published: (2025-01-01) -
CleanSheet: Advancing backdoor attack techniques for deep neural networks with stealthy trigger embedding
by: Ahmed Bensaoud, et al.
Published: (2025-12-01) -
Natural Occlusion-Based Backdoor Attacks: A Novel Approach to Compromising Pedestrian Detectors
by: Qiong Li, et al.
Published: (2025-07-01) -
Backdoor Attack Based on Lossy Image Compression Using Discrete Cosine Transform
by: Yuting Liu, et al.
Published: (2024-01-01) -
Improved Distributed Backdoor Attacks in Federated Learning by Density-Adaptive Data Poisoning and Projection-Based Gradient Updating
by: Jian Wang, et al.
Published: (2025-01-01)