Bitstream Collisions in Neural Image Compression via Adversarial Perturbations
Fuente:
arXiv
Saved in:
| Main Authors: | Madden, Jordan, Dorje, Lhamo, Li, Xiaohua |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adversarial Robustness of Near-Field Millimeter-Wave Imaging under Waveform-Domain Attacks
by: Dorje, Lhamo, et al.
Published: (2026)
by: Dorje, Lhamo, et al.
Published: (2026)
Robustness of Practical Perceptual Hashing Algorithms to Hash-Evasion and Hash-Inversion Attacks
by: Madden, Jordan, et al.
Published: (2024)
by: Madden, Jordan, et al.
Published: (2024)
Joint Universal Adversarial Perturbations with Interpretations
by: Ning, Liang-bo, et al.
Published: (2024)
by: Ning, Liang-bo, et al.
Published: (2024)
On the Feasibility of Poisoning Text-to-Image AI Models via Adversarial Mislabeling
by: Wu, Stanley, et al.
Published: (2025)
by: Wu, Stanley, 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)
BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron
by: Miah, Abdullah Arafat, et al.
Published: (2026)
by: Miah, Abdullah Arafat, et al.
Published: (2026)
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)
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)
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)
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)
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)
Quantifying the Noise of Structural Perturbations on Graph Adversarial Attacks
by: Fang, Junyuan, et al.
Published: (2025)
by: Fang, Junyuan, et al.
Published: (2025)
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)
Coward: Collision-based OOD Watermarking for Practical Proactive Federated Backdoor Detection
by: Li, Wenjie, et al.
Published: (2025)
by: Li, Wenjie, et al.
Published: (2025)
Semantic Router: On the Feasibility of Hijacking MLLMs via a Single Adversarial Perturbation
by: Li, Changyue, et al.
Published: (2025)
by: Li, Changyue, et al.
Published: (2025)
Neural Network Training on Encrypted Data with TFHE
by: Montero, Luis, et al.
Published: (2024)
by: Montero, Luis, et al.
Published: (2024)
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)
Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems
by: Balashov, Andrii, et al.
Published: (2025)
by: Balashov, Andrii, 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)
Quantifying Loss Aversion in Cyber Adversaries via LLM Analysis
by: Hans, Soham, et al.
Published: (2025)
by: Hans, Soham, 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)
Reflect-Guard: Enhancing LLM Safeguards against Adversarial Prompts via Logical Self-Reflection
by: Lin, Lixing, et al.
Published: (2026)
by: Lin, Lixing, 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)
Medical Multimodal Model Stealing Attacks via Adversarial Domain Alignment
by: Shen, Yaling, et al.
Published: (2025)
by: Shen, Yaling, 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)
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)
Character-Level Perturbations Disrupt LLM Watermarks
by: Zhang, Zhaoxi, et al.
Published: (2025)
by: Zhang, Zhaoxi, et al.
Published: (2025)
Security-aware Semantic-driven ISAC via Paired Adversarial Residual Networks
by: Liu, Yu, et al.
Published: (2025)
by: Liu, Yu, et al.
Published: (2025)
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)
From Similarity to Vulnerability: Key Collision Attack on LLM Semantic Caching
by: Zhang, Zhixiang, et al.
Published: (2026)
by: Zhang, Zhixiang, et al.
Published: (2026)
Adversarial Attack-Defense Co-Evolution for LLM Safety Alignment via Tree-Group Dual-Aware Search and Optimization
by: Li, Xurui, et al.
Published: (2025)
by: Li, Xurui, et al.
Published: (2025)
AdaDoS: Adaptive DoS Attack via Deep Adversarial Reinforcement Learning in SDN
by: Shao, Wei, et al.
Published: (2025)
by: Shao, Wei, et al.
Published: (2025)
PRM-Free Security Alignment of Large Models via Red Teaming and Adversarial Training
by: Du, Pengfei
Published: (2025)
by: Du, Pengfei
Published: (2025)
BESA: Boosting Encoder Stealing Attack with Perturbation Recovery
by: Ren, Xuhao, et al.
Published: (2025)
by: Ren, Xuhao, 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)
Self-interpreting Adversarial Images
by: Zhang, Tingwei, et al.
Published: (2024)
by: Zhang, Tingwei, et al.
Published: (2024)
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing
by: Gibert, Daniel, et al.
Published: (2024)
by: Gibert, Daniel, et al.
Published: (2024)
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)
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification
by: Kang, Mintong, et al.
Published: (2023)
by: Kang, Mintong, et al.
Published: (2023)
Similar Items
-
Adversarial Robustness of Near-Field Millimeter-Wave Imaging under Waveform-Domain Attacks
by: Dorje, Lhamo, et al.
Published: (2026) -
Robustness of Practical Perceptual Hashing Algorithms to Hash-Evasion and Hash-Inversion Attacks
by: Madden, Jordan, et al.
Published: (2024) -
Joint Universal Adversarial Perturbations with Interpretations
by: Ning, Liang-bo, et al.
Published: (2024) -
On the Feasibility of Poisoning Text-to-Image AI Models via Adversarial Mislabeling
by: Wu, Stanley, et al.
Published: (2025) -
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
by: Gao, Junqi, et al.
Published: (2024)