Adversarial Attacks to Latent Representations of Distributed Neural Networks in Split Computing
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Milin, Abdi, Mohammad, Ashdown, Jonathan, Restuccia, Francesco |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Resilience of Entropy Model in Distributed Neural Networks
by: Zhang, Milin, et al.
Published: (2024)
by: Zhang, Milin, et al.
Published: (2024)
DARDA: Domain-Aware Real-Time Dynamic Neural Network Adaptation
by: Rifat, Shahriar, et al.
Published: (2024)
by: Rifat, Shahriar, et al.
Published: (2024)
Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges
by: Zhang, Milin, et al.
Published: (2024)
by: Zhang, Milin, et al.
Published: (2024)
Semantic Multiplexing
by: Abdi, Mohammad, et al.
Published: (2025)
by: Abdi, Mohammad, et al.
Published: (2025)
SINF: Semantic Neural Network Inference with Semantic Subgraphs
by: Sayyed, A. Q. M. Sazzad, et al.
Published: (2023)
by: Sayyed, A. Q. M. Sazzad, et al.
Published: (2023)
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
by: Bortolussi, Luca, et al.
Published: (2022)
by: Bortolussi, Luca, et al.
Published: (2022)
GAIM: Attacking Graph Neural Networks via Adversarial Influence Maximization
by: Yang, Xiaodong, et al.
Published: (2024)
by: Yang, Xiaodong, et al.
Published: (2024)
Adversarial Attacks on Hyperbolic Networks
by: van Spengler, Max, et al.
Published: (2024)
by: van Spengler, Max, et al.
Published: (2024)
Forward-Forward Learning achieves Highly Selective Latent Representations for Out-of-Distribution Detection in Fully Spiking Neural Networks
by: Terres-Escudero, Erik B., et al.
Published: (2024)
by: Terres-Escudero, Erik B., et al.
Published: (2024)
Design Rules for Extreme-Edge Scientific Computing on AI Engines
by: Ma, Zhenghua, et al.
Published: (2026)
by: Ma, Zhenghua, et al.
Published: (2026)
Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective
by: Duan, Tianyang, et al.
Published: (2025)
by: Duan, Tianyang, et al.
Published: (2025)
GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
by: Cui, Canyixing, et al.
Published: (2026)
by: Cui, Canyixing, et al.
Published: (2026)
Fine-Grained Iterative Adversarial Attacks with Limited Computation Budget
by: Hou, Zhichao, et al.
Published: (2025)
by: Hou, Zhichao, et al.
Published: (2025)
Studying the Impact of Latent Representations in Implicit Neural Networks for Scientific Continuous Field Reconstruction
by: Xu, Wei, et al.
Published: (2024)
by: Xu, Wei, et al.
Published: (2024)
Efficient Adversarial Attacks on High-dimensional Offline Bandits
by: Hosseini, Seyed Mohammad Hadi, et al.
Published: (2026)
by: Hosseini, Seyed Mohammad Hadi, et al.
Published: (2026)
SplitQuant: Layer Splitting for Low-Bit Neural Network Quantization
by: Song, Jaewoo, et al.
Published: (2025)
by: Song, Jaewoo, et al.
Published: (2025)
Understanding Adversarial Transfer: Why Representation-Space Attacks Fail Where Data-Space Attacks Succeed
by: Gupta, Isha, et al.
Published: (2025)
by: Gupta, Isha, et al.
Published: (2025)
Low-Rank Adversarial PGD Attack
by: Savostianova, Dayana, et al.
Published: (2024)
by: Savostianova, Dayana, et al.
Published: (2024)
Unifying Adversarial Perturbation for Graph Neural Networks
by: Yang, Jinluan, et al.
Published: (2025)
by: Yang, Jinluan, et al.
Published: (2025)
Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning
by: Rossolini, Giulio, et al.
Published: (2025)
by: Rossolini, Giulio, et al.
Published: (2025)
Hide and Find: A Distributed Adversarial Attack on Federated Graph Learning
by: Liu, Jinshan, et al.
Published: (2026)
by: Liu, Jinshan, et al.
Published: (2026)
Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks
by: Panda, Deepak Kumar, et al.
Published: (2025)
by: Panda, Deepak Kumar, et al.
Published: (2025)
Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)
by: Kofinas, Miltiadis, et al.
Published: (2024)
Multi-Layer Confidence Scoring for Detection of Out-of-Distribution Samples, Adversarial Attacks, and In-Distribution Misclassifications
by: Capelli, Lorenzo, et al.
Published: (2025)
by: Capelli, Lorenzo, et al.
Published: (2025)
Bridging Theory and Practice in Link Representation with Graph Neural Networks
by: Lachi, Veronica, et al.
Published: (2025)
by: Lachi, Veronica, et al.
Published: (2025)
Latent Communication in Artificial Neural Networks
by: Moschella, Luca
Published: (2024)
by: Moschella, Luca
Published: (2024)
Resilience and Security of Deep Neural Networks Against Intentional and Unintentional Perturbations: Survey and Research Challenges
by: Sayyed, Sazzad, et al.
Published: (2024)
by: Sayyed, Sazzad, et al.
Published: (2024)
Understanding Task Representations in Neural Networks via Bayesian Ablation
by: Nam, Andrew, et al.
Published: (2025)
by: Nam, Andrew, et al.
Published: (2025)
Disttack: Graph Adversarial Attacks Toward Distributed GNN Training
by: Zhang, Yuxiang, et al.
Published: (2024)
by: Zhang, Yuxiang, et al.
Published: (2024)
An Unsupervised Adversarial Autoencoder for Cyber Attack Detection in Power Distribution Grids
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)
Hetero-SplitEE: Split Learning of Neural Networks with Early Exits for Heterogeneous IoT Devices
by: Oda, Yuki, et al.
Published: (2025)
by: Oda, Yuki, et al.
Published: (2025)
Latent Adversarial Regularization for Offline Preference Optimization
by: Jiang, Enyi, et al.
Published: (2026)
by: Jiang, Enyi, et al.
Published: (2026)
Input-Specific and Universal Adversarial Attack Generation for Spiking Neural Networks in the Spiking Domain
by: Raptis, Spyridon, et al.
Published: (2025)
by: Raptis, Spyridon, et al.
Published: (2025)
Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
by: Mukherjee, Kunal, et al.
Published: (2026)
by: Mukherjee, Kunal, et al.
Published: (2026)
Towards Reliable Evaluation of Adversarial Robustness for Spiking Neural Networks
by: Wang, Jihang, et al.
Published: (2025)
by: Wang, Jihang, et al.
Published: (2025)
Understanding Model Ensemble in Transferable Adversarial Attack
by: Yao, Wei, et al.
Published: (2024)
by: Yao, Wei, et al.
Published: (2024)
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
by: Feng, Yunzhen, et al.
Published: (2024)
by: Feng, Yunzhen, et al.
Published: (2024)
HealSplit: Towards Self-Healing through Adversarial Distillation in Split Federated Learning
by: Xie, Yuhan, et al.
Published: (2025)
by: Xie, Yuhan, et al.
Published: (2025)
Adaptive Learning of the Latent Space of Wasserstein Generative Adversarial Networks
by: Qiu, Yixuan, et al.
Published: (2024)
by: Qiu, Yixuan, et al.
Published: (2024)
Gradient Inversion Attack on Graph Neural Networks
by: Sinha, Divya Anand, et al.
Published: (2024)
by: Sinha, Divya Anand, et al.
Published: (2024)
Similar Items
-
Resilience of Entropy Model in Distributed Neural Networks
by: Zhang, Milin, et al.
Published: (2024) -
DARDA: Domain-Aware Real-Time Dynamic Neural Network Adaptation
by: Rifat, Shahriar, et al.
Published: (2024) -
Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges
by: Zhang, Milin, et al.
Published: (2024) -
Semantic Multiplexing
by: Abdi, Mohammad, et al.
Published: (2025) -
SINF: Semantic Neural Network Inference with Semantic Subgraphs
by: Sayyed, A. Q. M. Sazzad, et al.
Published: (2023)