Cover Image

Robust Subgraph Learning by Monitoring Early Training Representations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Neshatfar, Sepideh, Sekeh, Salimeh Yasaei
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FogGuard: guarding YOLO against fog using perceptual loss
by: Gharatappeh, Soheil, et al.
Published: (2024)

Information Consistent Pruning: How to Efficiently Search for Sparse Networks?
by: Gharatappeh, Soheil, et al.
Published: (2025)

Ghost-Connect Net: A Generalization-Enhanced Guidance For Sparse Deep Networks Under Distribution Shifts
by: Wisell, Mary Isabelle, et al.
Published: (2024)

Towards Explaining Deep Neural Network Compression Through a Probabilistic Latent Space
by: Mozafari-Nia, Mahsa, et al.
Published: (2024)

DRGW: Learning Disentangled Representations for Robust Graph Watermarking
by: Li, Jiasen, et al.
Published: (2026)

TREC: APT Tactic / Technique Recognition via Few-Shot Provenance Subgraph Learning
by: Lv, Mingqi, et al.
Published: (2024)

Learning Robust and Privacy-Preserving Representations via Information Theory
by: Zhang, Binghui, et al.
Published: (2024)

Dual Explanations via Subgraph Matching for Malware Detection
by: Shokouhinejad, Hossein, et al.
Published: (2025)

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers
by: Liu, Dongyi, et al.
Published: (2025)

Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates
by: Angioni, Daniele, et al.
Published: (2024)

On Using Certified Training towards Empirical Robustness
by: De Palma, Alessandro, et al.
Published: (2024)

Vulnerability-Aware Robust Multimodal Adversarial Training
by: Zhang, Junrui, et al.
Published: (2025)

Deep Efficient Private Neighbor Generation for Subgraph Federated Learning
by: Zhang, Ke, et al.
Published: (2024)

Detecting Sybil Addresses in Blockchain Airdrops: A Subgraph-based Feature Propagation and Fusion Approach
by: Liu, Qiangqiang, et al.
Published: (2025)

Towards Generalized Certified Robustness with Multi-Norm Training
by: Jiang, Enyi, et al.
Published: (2024)

OCR-APT: Reconstructing APT Stories from Audit Logs using Subgraph Anomaly Detection and LLMs
by: Aly, Ahmed, et al.
Published: (2025)

Robust Backdoor Removal by Reconstructing Trigger-Activated Changes in Latent Representation
by: Iwahana, Kazuki, et al.
Published: (2025)

Same Payload, Different Channel: Measuring Trust Asymmetry in Tool-Using Language Models
by: Syed, Mohammed Sameer, et al.
Published: (2026)

WebGuard++:Interpretable Malicious URL Detection via Bidirectional Fusion of HTML Subgraphs and Multi-Scale Convolutional BERT
by: Tian, Ye, et al.
Published: (2025)

Adaptive Meta-learning-based Adversarial Training for Robust Automatic Modulation Classification
by: Bamdad, Amirmohammad, et al.
Published: (2025)

On the Conflict of Robustness and Learning in Collaborative Machine Learning
by: Raynal, Mathilde, et al.
Published: (2024)

How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?
by: Liu, Meiqi, et al.
Published: (2025)

DeepTrust: Multi-Step Classification through Dissimilar Adversarial Representations for Robust Android Malware Detection
by: Pulido-Cortázar, Daniel, et al.
Published: (2025)

Evaluating Tabular Representation Learning for Network Intrusion Detection
by: Butt, Muhammad Usman, et al.
Published: (2026)

Black-Box Privacy Attacks on Shared Representations in Multitask Learning
by: Abascal, John, et al.
Published: (2025)

Self-Supervised Learning of Graph Representations for Network Intrusion Detection
by: Guerra, Lorenzo, et al.
Published: (2025)

Attesting Distributional Properties of Training Data for Machine Learning
by: Duddu, Vasisht, et al.
Published: (2023)

On the Query Complexity of Training Data Reconstruction in Private Learning
by: Mukherjee, Prateeti, et al.
Published: (2023)

Plinius: Secure and Persistent Machine Learning Model Training
by: Yuhala, Peterson, et al.
Published: (2021)

On the Robustness of Distributed Machine Learning against Transfer Attacks
by: Andreina, Sébastien, et al.
Published: (2024)

Improving Intrusion Detection with Domain-Invariant Representation Learning in Latent Space
by: Roy, Padmaksha, et al.
Published: (2023)

On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
by: Thaker, Pratiksha, et al.
Published: (2023)

INTACT: Intent-Aware Representation Learning for Cryptographic Traffic Violation Detection
by: Ray, Rahul D
Published: (2026)

Covert Attacks on Machine Learning Training in Passively Secure MPC
by: Jagielski, Matthew, et al.
Published: (2025)

Monitor and Recover: A Paradigm for Future Research on Distribution Shift in Learning-Enabled Cyber-Physical Systems
by: Lin, Vivian, et al.
Published: (2025)

ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning
by: Floris, Giuseppe, et al.
Published: (2023)

SLVR: Securely Leveraging Client Validation for Robust Federated Learning
by: Choi, Jihye, et al.
Published: (2025)

Confundo: Learning to Generate Robust Poison for Practical RAG Systems
by: Hu, Haoyang, et al.
Published: (2026)

Robustness of Selected Learning Models under Label-Flipping Attack
by: Bhargava, Sarvagya, et al.
Published: (2025)

FedRE: Robust and Effective Federated Learning with Privacy Preference
by: Xiao, Tianzhe, et al.
Published: (2025)