Joint Universal Adversarial Perturbations with Interpretations
Fuente:
arXiv
Saved in:
| Main Authors: | Ning, Liang-bo, Dai, Zeyu, Fan, Wenqi, Su, Jingran, Pan, Chao, Wang, Luning, Li, Qing |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent
by: Ning, Liang-bo, et al.
Published: (2025)
by: Ning, Liang-bo, et al.
Published: (2025)
Exploring Backdoor Attack and Defense for LLM-empowered Recommendations
by: Ning, Liangbo, et al.
Published: (2025)
by: Ning, Liangbo, et al.
Published: (2025)
Bitstream Collisions in Neural Image Compression via Adversarial Perturbations
by: Madden, Jordan, et al.
Published: (2025)
by: Madden, Jordan, et al.
Published: (2025)
Backdoor Graph Condensation
by: Wu, Jiahao, et al.
Published: (2024)
by: Wu, Jiahao, et al.
Published: (2024)
Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations
by: Oskouie, Haniyeh Ehsani, et al.
Published: (2022)
by: Oskouie, Haniyeh Ehsani, et al.
Published: (2022)
A Novel and Practical Universal Adversarial Perturbations against Deep Reinforcement Learning based Intrusion Detection Systems
by: Zhang, H., et al.
Published: (2025)
by: Zhang, H., et al.
Published: (2025)
From Allies to Adversaries: Manipulating LLM Tool-Calling through Adversarial Injection
by: Wang, Haowei, et al.
Published: (2024)
by: Wang, Haowei, et al.
Published: (2024)
From Pixels to Trajectory: Universal Adversarial Example Detection via Temporal Imprints
by: Gao, Yansong, et al.
Published: (2025)
by: Gao, Yansong, et al.
Published: (2025)
Joint-GCG: Unified Gradient-Based Poisoning Attacks on Retrieval-Augmented Generation Systems
by: Wang, Haowei, et al.
Published: (2025)
by: Wang, Haowei, et al.
Published: (2025)
ExplainableGuard: Interpretable Adversarial Defense for Large Language Models Using Chain-of-Thought Reasoning
by: Guan, Shaowei, et al.
Published: (2025)
by: Guan, Shaowei, et al.
Published: (2025)
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
by: Gao, Junqi, et al.
Published: (2024)
by: Gao, Junqi, et al.
Published: (2024)
BESA: Boosting Encoder Stealing Attack with Perturbation Recovery
by: Ren, Xuhao, et al.
Published: (2025)
by: Ren, Xuhao, et al.
Published: (2025)
Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations
by: Acharya, Pawan, et al.
Published: (2026)
by: Acharya, Pawan, et al.
Published: (2026)
Multi-Stream Perturbation Attack: Breaking Safety Alignment of Thinking LLMs Through Concurrent Task Interference
by: Yang, Fan
Published: (2026)
by: Yang, Fan
Published: (2026)
Comprehensive Botnet Detection by Mitigating Adversarial Attacks, Navigating the Subtleties of Perturbation Distances and Fortifying Predictions with Conformal Layers
by: Yumlembam, Rahul, et al.
Published: (2024)
by: Yumlembam, Rahul, et al.
Published: (2024)
Character-Level Perturbations Disrupt LLM Watermarks
by: Zhang, Zhaoxi, et al.
Published: (2025)
by: Zhang, Zhaoxi, et al.
Published: (2025)
Quantifying the Noise of Structural Perturbations on Graph Adversarial Attacks
by: Fang, Junyuan, et al.
Published: (2025)
by: Fang, Junyuan, et al.
Published: (2025)
CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations
by: Li, Xiaohu, et al.
Published: (2025)
by: Li, Xiaohu, et al.
Published: (2025)
DCVD: Dual-Channel Cross-Modal Fusion for Joint Vulnerability Detection and Localization
by: Tang, Wenxin, et al.
Published: (2026)
by: Tang, Wenxin, et al.
Published: (2026)
Enhancing Adversarial Resistance in LLMs with Recursion
by: Li, Bryan, et al.
Published: (2024)
by: Li, Bryan, et al.
Published: (2024)
Preventing Non-intrusive Load Monitoring Privacy Invasion: A Precise Adversarial Attack Scheme for Networked Smart Meters
by: He, Jialing, et al.
Published: (2024)
by: He, Jialing, et al.
Published: (2024)
Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models
by: Ma, Jiachen, et al.
Published: (2024)
by: Ma, Jiachen, et al.
Published: (2024)
Discovering Universal Semantic Triggers for Text-to-Image Synthesis
by: Zhai, Shengfang, et al.
Published: (2024)
by: Zhai, Shengfang, et al.
Published: (2024)
Adversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigation
by: Ndayipfukamiye, Tharcisse, et al.
Published: (2025)
by: Ndayipfukamiye, Tharcisse, et al.
Published: (2025)
CyberEvolver: Structured Self-Evolution for Cybersecurity Agents On the Fly
by: Fan, Yihe, et al.
Published: (2026)
by: Fan, Yihe, et al.
Published: (2026)
Modeling the Attack: Detecting AI-Generated Text by Quantifying Adversarial Perturbations
by: Teja, Lekkala Sai, et al.
Published: (2025)
by: Teja, Lekkala Sai, et al.
Published: (2025)
Security of Internet of Agents: Attacks and Countermeasures
by: Wang, Yuntao, et al.
Published: (2025)
by: Wang, Yuntao, et al.
Published: (2025)
Probing Latent Subspaces in LLM for AI Security: Identifying and Manipulating Adversarial States
by: Chia, Xin Wei, et al.
Published: (2025)
by: Chia, Xin Wei, et al.
Published: (2025)
Fight Perturbations with Perturbations: Defending Adversarial Attacks via Neuron Influence
by: Chen, Ruoxi, et al.
Published: (2021)
by: Chen, Ruoxi, et al.
Published: (2021)
Emoti-Attack: Zero-Perturbation Adversarial Attacks on NLP Systems via Emoji Sequences
by: Zhang, Yangshijie
Published: (2025)
by: Zhang, Yangshijie
Published: (2025)
VisInject: Disruption != Injection -- A Dual-Dimension Evaluation of Universal Adversarial Attacks on Vision-Language Models
by: Liu, Pang, et al.
Published: (2026)
by: Liu, Pang, et al.
Published: (2026)
NCCR: to Evaluate the Robustness of Neural Networks and Adversarial Examples
by: Pu, Shi, et al.
Published: (2025)
by: Pu, Shi, et al.
Published: (2025)
Backdoor Samples Detection Based on Perturbation Discrepancy Consistency in Pre-trained Language Models
by: Peng, Zuquan, et al.
Published: (2025)
by: Peng, Zuquan, et al.
Published: (2025)
Co-Evolutionary Multi-Modal Alignment via Structured Adversarial Evolution
by: Shi, Guoxin, et al.
Published: (2026)
by: Shi, Guoxin, et al.
Published: (2026)
FastFHE: Packing-Scalable and Depthwise-Separable CNN Inference Over FHE
by: Song, Wenbo, et al.
Published: (2025)
by: Song, Wenbo, et al.
Published: (2025)
A Novel Perturb-ability Score to Mitigate Evasion Adversarial Attacks on Flow-Based ML-NIDS
by: elShehaby, Mohamed, et al.
Published: (2024)
by: elShehaby, Mohamed, et al.
Published: (2024)
Measuring the Robustness of Audio Deepfake Detectors
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification
by: Kang, Mintong, et al.
Published: (2023)
by: Kang, Mintong, et al.
Published: (2023)
JADES: A Universal Framework for Jailbreak Assessment via Decompositional Scoring
by: Chu, Junjie, et al.
Published: (2025)
by: Chu, Junjie, et al.
Published: (2025)
SEASONED: Semantic-Enhanced Self-Counterfactual Explainable Detection of Adversarial Exploiter Contracts
by: Ai, Xng, et al.
Published: (2025)
by: Ai, Xng, et al.
Published: (2025)
Similar Items
-
CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent
by: Ning, Liang-bo, et al.
Published: (2025) -
Exploring Backdoor Attack and Defense for LLM-empowered Recommendations
by: Ning, Liangbo, et al.
Published: (2025) -
Bitstream Collisions in Neural Image Compression via Adversarial Perturbations
by: Madden, Jordan, et al.
Published: (2025) -
Backdoor Graph Condensation
by: Wu, Jiahao, et al.
Published: (2024) -
Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations
by: Oskouie, Haniyeh Ehsani, et al.
Published: (2022)