Saved in:
| Main Authors: | Kulkarni, Prashant, Namer, Assaf |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.15560 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Jailbreak Attacks and Defenses Against Large Language Models: A Survey
by: Yi, Sibo, et al.
Published: (2024)
by: Yi, Sibo, et al.
Published: (2024)
A Multi-Agent LLM Defense Pipeline Against Prompt Injection Attacks
by: Hossain, S M Asif, et al.
Published: (2025)
by: Hossain, S M Asif, et al.
Published: (2025)
PECAN: A Deterministic Certified Defense Against Backdoor Attacks
by: Zhang, Yuhao, et al.
Published: (2023)
by: Zhang, Yuhao, et al.
Published: (2023)
A Zero Trust Framework for Realization and Defense Against Generative AI Attacks in Power Grid
by: Munir, Md. Shirajum, et al.
Published: (2024)
by: Munir, Md. Shirajum, et al.
Published: (2024)
A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?
by: elShehaby, Mohamed, et al.
Published: (2026)
by: elShehaby, Mohamed, et al.
Published: (2026)
A Systematic Review of Poisoning Attacks Against Large Language Models
by: Fendley, Neil, et al.
Published: (2025)
by: Fendley, Neil, et al.
Published: (2025)
A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems
by: Tafreshian, Benyamin, et al.
Published: (2025)
by: Tafreshian, Benyamin, et al.
Published: (2025)
Attacks and Defenses Against LLM Fingerprinting
by: Kurian, Kevin, et al.
Published: (2025)
by: Kurian, Kevin, et al.
Published: (2025)
Dashed Line Defense: Plug-And-Play Defense Against Adaptive Score-Based Query Attacks
by: Fu, Yanzhang, et al.
Published: (2026)
by: Fu, Yanzhang, et al.
Published: (2026)
Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents
by: Zhan, Qiusi, et al.
Published: (2025)
by: Zhan, Qiusi, et al.
Published: (2025)
A Survey on Model Extraction Attacks and Defenses for Large Language Models
by: Zhao, Kaixiang, et al.
Published: (2025)
by: Zhao, Kaixiang, et al.
Published: (2025)
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation
by: Pham, Dzung, et al.
Published: (2023)
by: Pham, Dzung, et al.
Published: (2023)
SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
by: Paracha, Anum, et al.
Published: (2025)
by: Paracha, Anum, et al.
Published: (2025)
Optimal Defenses Against Gradient Reconstruction Attacks
by: Chen, Yuxiao, et al.
Published: (2024)
by: Chen, Yuxiao, et al.
Published: (2024)
KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
Defending Large Language Models Against Attacks With Residual Stream Activation Analysis
by: Kawasaki, Amelia, et al.
Published: (2024)
by: Kawasaki, Amelia, et al.
Published: (2024)
MISLEAD: Manipulating Importance of Selected features for Learning Epsilon in Evasion Attack Deception
by: Khazanchi, Vidit, et al.
Published: (2024)
by: Khazanchi, Vidit, et al.
Published: (2024)
Membership Inference Attacks for Retrieval Based In-Context Learning for Document Question Answering
by: Kulkarni, Tejas, et al.
Published: (2026)
by: Kulkarni, Tejas, et al.
Published: (2026)
Composite Backdoor Attacks Against Large Language Models
by: Huang, Hai, et al.
Published: (2023)
by: Huang, Hai, et al.
Published: (2023)
Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey
by: Huang, Tiansheng, et al.
Published: (2024)
by: Huang, Tiansheng, et al.
Published: (2024)
Learning to Poison Large Language Models for Downstream Manipulation
by: Zhou, Xiangyu, et al.
Published: (2024)
by: Zhou, Xiangyu, et al.
Published: (2024)
Hijacking Large Language Models via Adversarial In-Context Learning
by: Zhou, Xiangyu, et al.
Published: (2023)
by: Zhou, Xiangyu, et al.
Published: (2023)
Self-Evaluation as a Defense Against Adversarial Attacks on LLMs
by: Brown, Hannah, et al.
Published: (2024)
by: Brown, Hannah, et al.
Published: (2024)
Attacking LLMs and AI Agents: Advertisement Embedding Attacks Against Large Language Models
by: Guo, Qiming, et al.
Published: (2025)
by: Guo, Qiming, et al.
Published: (2025)
Attack and Defense of Deep Learning Models in the Field of Web Attack Detection
by: Shi, Lijia, et al.
Published: (2024)
by: Shi, Lijia, et al.
Published: (2024)
The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections
by: Nasr, Milad, et al.
Published: (2025)
by: Nasr, Milad, et al.
Published: (2025)
Dummy-Aware Weighted Attack (DAWA): Breaking the Safe Sink in Dummy Class Defenses
by: Yu, Yunrui, et al.
Published: (2026)
by: Yu, Yunrui, et al.
Published: (2026)
A Taxonomy of Attacks and Defenses in Split Learning
by: Shabbir, Aqsa, et al.
Published: (2025)
by: Shabbir, Aqsa, et al.
Published: (2025)
A New Federated Learning Framework Against Gradient Inversion Attacks
by: Guo, Pengxin, et al.
Published: (2024)
by: Guo, Pengxin, et al.
Published: (2024)
LeakSealer: A Semisupervised Defense for LLMs Against Prompt Injection and Leakage Attacks
by: Panebianco, Francesco, et al.
Published: (2025)
by: Panebianco, Francesco, et al.
Published: (2025)
ADAGE: Active Defenses Against GNN Extraction
by: Xu, Jing, et al.
Published: (2025)
by: Xu, Jing, et al.
Published: (2025)
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024)
by: Zeng, Yifan, et al.
Published: (2024)
SOS! Soft Prompt Attack Against Open-Source Large Language Models
by: Yang, Ziqing, et al.
Published: (2024)
by: Yang, Ziqing, et al.
Published: (2024)
Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement
by: Kim, Heegyu, et al.
Published: (2024)
by: Kim, Heegyu, et al.
Published: (2024)
CAPoW: Context-Aware AI-Assisted Proof of Work based DDoS Defense
by: Chakraborty, Trisha, et al.
Published: (2023)
by: Chakraborty, Trisha, et al.
Published: (2023)
Data-free Defense of Black Box Models Against Adversarial Attacks
by: Nayak, Gaurav Kumar, et al.
Published: (2022)
by: Nayak, Gaurav Kumar, et al.
Published: (2022)
MM-FusionNet: Context-Aware Dynamic Fusion for Multi-modal Fake News Detection with Large Vision-Language Models
by: He, Junhao, et al.
Published: (2025)
by: He, Junhao, et al.
Published: (2025)
Steering Dialogue Dynamics for Robustness against Multi-turn Jailbreaking Attacks
by: Hu, Hanjiang, et al.
Published: (2025)
by: Hu, Hanjiang, et al.
Published: (2025)
FedMID: A Data-Free Method for Using Intermediate Outputs as a Defense Mechanism Against Poisoning Attacks in Federated Learning
by: Han, Sungwon, et al.
Published: (2024)
by: Han, Sungwon, et al.
Published: (2024)
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
by: Liu, Sheng, et al.
Published: (2024)
by: Liu, Sheng, et al.
Published: (2024)
Similar Items
-
Jailbreak Attacks and Defenses Against Large Language Models: A Survey
by: Yi, Sibo, et al.
Published: (2024) -
A Multi-Agent LLM Defense Pipeline Against Prompt Injection Attacks
by: Hossain, S M Asif, et al.
Published: (2025) -
PECAN: A Deterministic Certified Defense Against Backdoor Attacks
by: Zhang, Yuhao, et al.
Published: (2023) -
A Zero Trust Framework for Realization and Defense Against Generative AI Attacks in Power Grid
by: Munir, Md. Shirajum, et al.
Published: (2024) -
A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?
by: elShehaby, Mohamed, et al.
Published: (2026)