Cover Image

TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hossain, Khondoker Murad, Oates, Tim
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks
by: Hossain, Khondoker Murad, et al.
Published: (2024)

Invisible Backdoor Attack Through Singular Value Decomposition
by: Chen, Wenmin, et al.
Published: (2024)

ReVeil: Unconstrained Concealed Backdoor Attack on Deep Neural Networks using Machine Unlearning
by: Alam, Manaar, et al.
Published: (2025)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)

Unlearn to Relearn Backdoors: Deferred Backdoor Functionality Attacks on Deep Learning Models
by: Shin, Jeongjin, et al.
Published: (2024)

Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection
by: Alam, Mohammad Mahmudul, et al.
Published: (2024)

Detecting and Eliminating Neural Network Backdoors Through Active Paths with Application to Intrusion Detection
by: Høyheim, Eirik, et al.
Published: (2026)

Backdoor Attacks on Fault Detection and Localization in Cyber-Physical Systems
by: Jean, Abile, et al.
Published: (2026)

Heterogeneous Graph Backdoor Attack
by: Chen, Jiawei, et al.
Published: (2025)

Backdoor Vectors: a Task Arithmetic View on Backdoor Attacks and Defenses
by: Pawlak, Stanisław, et al.
Published: (2025)

Mitigating Deep Reinforcement Learning Backdoors in the Neural Activation Space
by: Vyas, Sanyam, et al.
Published: (2024)

UNIDOOR: A Universal Framework for Action-Level Backdoor Attacks in Deep Reinforcement Learning
by: Ma, Oubo, et al.
Published: (2025)

A Semantic and Clean-label Backdoor Attack against Graph Convolutional Networks
by: Dai, Jiazhu, et al.
Published: (2025)

Backdoor Attacks on Deep Learning Face Detection
by: Roux, Quentin Le, et al.
Published: (2025)

Compromising Embodied Agents with Contextual Backdoor Attacks
by: Liu, Aishan, et al.
Published: (2024)

BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting
by: Lin, Xiao, et al.
Published: (2024)

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
by: Ren, Zhiyao, et al.
Published: (2025)

Structure-Aware Distributed Backdoor Attacks in Federated Learning
by: Jian, Wang, et al.
Published: (2026)

Client-Side Patching against Backdoor Attacks in Federated Learning
by: Molina-Coronado, Borja
Published: (2024)

Your Agent Can Defend Itself against Backdoor Attacks
by: Changjiang, Li, et al.
Published: (2025)

Exploiting Layer-Specific Vulnerabilities to Backdoor Attack in Federated Learning
by: Foroughi, Mohammad Hadi, et al.
Published: (2026)

Revisiting Backdoor Attacks on Time Series Classification in the Frequency Domain
by: Huang, Yuanmin, et al.
Published: (2025)

BLAST: A Stealthy Backdoor Leverage Attack against Cooperative Multi-Agent Deep Reinforcement Learning based Systems
by: Fang, Jing, et al.
Published: (2025)

Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
by: Mukherjee, Kunal, et al.
Published: (2026)

The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers
by: Mengara, Orson
Published: (2024)

LoBAM: LoRA-Based Backdoor Attack on Model Merging
by: Yin, Ming, et al.
Published: (2024)

Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs
by: Wang, Yifei, et al.
Published: (2026)

BadImplant: Injection-based Multi-Targeted Graph Backdoor Attack
by: Khan, Md Nabi Newaz, et al.
Published: (2026)

Evaluating False Alarm and Missing Attacks in CAN IDS
by: Hossain, Nirab, et al.
Published: (2026)

Unlearning Inversion Attacks for Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2025)

On the Robustness of Bayesian Neural Networks to Adversarial Attacks
by: Bortolussi, Luca, et al.
Published: (2022)

Fingerprinting Deep Learning Models via Network Traffic Patterns in Federated Learning
by: Shuvo, Md Nahid Hasan, et al.
Published: (2025)

Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)

Defending the Edge: Representative-Attention Defense against Backdoor Attacks in Federated Learning
by: Obioma, Chibueze Peace, et al.
Published: (2025)

Strategic Sample Selection for Improved Clean-Label Backdoor Attacks in Text Classification
by: Kirci, Onur Alp, et al.
Published: (2025)

Backdoor Attack against One-Class Sequential Anomaly Detection Models
by: Cheng, He, et al.
Published: (2024)

TrojFM: Resource-efficient Backdoor Attacks against Very Large Foundation Models
by: Nie, Yuzhou., et al.
Published: (2024)

DeBUGCN -- Detecting Backdoors in CNNs Using Graph Convolutional Networks
by: Vartak, Akash, et al.
Published: (2025)

Enhancing IoT Cyber Attack Detection in the Presence of Highly Imbalanced Data
by: Haque, Md. Ehsanul, et al.
Published: (2025)

Rounding-Guided Backdoor Injection in Deep Learning Model Quantization
by: Chen, Xiangxiang, et al.
Published: (2025)