Cover Image

Adversarial Attacks on Large Language Models Using Regularized Relaxation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chacko, Samuel Jacob, Biswas, Sajib, Islam, Chashi Mahiul, Liza, Fatema Tabassum, Liu, Xiuwen
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computation and Language Cryptography and Security I.2.7
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
by: Biswas, Sajib, et al.
Published: (2025)

Evaluating the Robustness of Large Language Model Safety Guardrails Against Adversarial Attacks
by: Young, Richard J.
Published: (2025)

Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs)
by: Verma, Apurv, et al.
Published: (2024)

UniC-RAG: Universal Knowledge Corruption Attacks to Retrieval-Augmented Generation
by: Geng, Runpeng, et al.
Published: (2025)

sudoLLM: On Multi-role Alignment of Language Models
by: Saha, Soumadeep, et al.
Published: (2025)

Defending against Backdoor Attacks via Module Switching
by: Li, Weijun, et al.
Published: (2025)

POISONCRAFT: Practical Poisoning of Retrieval-Augmented Generation for Large Language Models
by: Shao, Yangguang, et al.
Published: (2025)

Large Language Models are Advanced Anonymizers
by: Staab, Robin, et al.
Published: (2024)

A Semantic Invariant Robust Watermark for Large Language Models
by: Liu, Aiwei, et al.
Published: (2023)

Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?
by: Xin, Yuan, et al.
Published: (2025)

Blind Spots in the Guard: How Domain-Camouflaged Injection Attacks Evade Detection in Multi-Agent LLM Systems
by: Pai, Aaditya
Published: (2026)

Benchmarking Large Language Models for IoC Recovery under Adversarial Code Obfuscation and Encryption
by: Morales, Jaime, et al.
Published: (2026)

Watermarking Degrades Alignment in Language Models: Analysis and Mitigation
by: Verma, Apurv, et al.
Published: (2025)

GuardVal: Dynamic Large Language Model Jailbreak Evaluation for Comprehensive Safety Testing
by: Zhang, Peiyan, et al.
Published: (2025)

ConfusionPrompt: Practical Private Inference for Online Large Language Models
by: Mai, Peihua, et al.
Published: (2023)

DWFS-Obfuscation: Dynamic Weighted Feature Selection for Robust Malware Familial Classification under Obfuscation
by: Wei, Xingyuan, et al.
Published: (2025)

Safeguarding Efficacy in Large Language Models: Evaluating Resistance to Human-Written and Algorithmic Adversarial Prompts
by: Downey-Webb, Tiarnaigh, et al.
Published: (2025)

Real AI Agents with Fake Memories: Fatal Context Manipulation Attacks on Web3 Agents
by: Patlan, Atharv Singh, et al.
Published: (2025)

Detecting Prompt Injection Attacks Against Application Using Classifiers
by: Shaheer, Safwan, et al.
Published: (2025)

Unlocking the Potential of Large Language Models for Clinical Text Anonymization: A Comparative Study
by: Pissarra, David, et al.
Published: (2024)

Temporal Attack Pattern Detection in Multi-Agent AI Workflows: An Open Framework for Training Trace-Based Security Models
by: Del Rosario, Ron F.
Published: (2025)

Ignore Me But Don't Replace Me: Utilizing Non-Linguistic Elements for Pretraining on the Cybersecurity Domain
by: Jang, Eugene, et al.
Published: (2024)

MarkLLM: An Open-Source Toolkit for LLM Watermarking
by: Pan, Leyi, et al.
Published: (2024)

Prompted Contextual Vectors for Spear-Phishing Detection
by: Nahmias, Daniel, et al.
Published: (2024)

Can Watermarked LLMs be Identified by Users via Crafted Prompts?
by: Liu, Aiwei, et al.
Published: (2024)

SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding
by: Mai, Peihua, et al.
Published: (2025)

PoTS: Proof-of-Training-Steps for Backdoor Detection in Large Language Models
by: Seddik, Issam, et al.
Published: (2025)

Beyond the Benchmark: Innovative Defenses Against Prompt Injection Attacks
by: Shaheer, Safwan, et al.
Published: (2025)

Predicting Known Vulnerabilities from Attack Descriptions Using Sentence Transformers
by: Othman, Refat
Published: (2026)

Scaling Trends in Language Model Robustness
by: Howe, Nikolaus, et al.
Published: (2024)

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

Reducing Information Overload: Because Even Security Experts Need to Blink
by: Kuehn, Philipp, et al.
Published: (2022)

Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients
by: Li, Weijun, et al.
Published: (2024)

Terrarium: Revisiting the Blackboard for Multi-Agent Safety, Privacy, and Security Studies
by: Nakamura, Mason, et al.
Published: (2025)

Adversarial Feeds Steer LLM Agent Decisions Against Their Defaults
by: Usman, Rana Muhammad
Published: (2026)

Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks
by: Kurian, Ashley, et al.
Published: (2025)

Split-and-Denoise: Protect large language model inference with local differential privacy
by: Mai, Peihua, et al.
Published: (2023)

Super Suffixes: Bypassing Text Generation Alignment and Guard Models Simultaneously
by: Adiletta, Andrew, et al.
Published: (2025)

AI Safeguards, Generative AI and the Pandora Box: AI Safety Measures to Protect Businesses and Personal Reputation
by: Kumar, Prasanna
Published: (2026)

Efficient LLM Safety Evaluation through Multi-Agent Debate
by: Lin, Dachuan, et al.
Published: (2025)