:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Duan, Donghang, Zheng, Xu, He, Yuefeng, Mu, Chong, Cai, Leyi, Zhang, Lizong
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Computation and Language
Online Access:	https://arxiv.org/abs/2512.06713
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Probe before You Talk: Towards Black-box Defense against Backdoor Unalignment for Large Language Models
by: Yi, Biao, et al.
Published: (2025)

A First Look at GPT Apps: Landscape and Vulnerability
by: Zhang, Zejun, et al.
Published: (2024)

LLM Anonymization Against Agentic Re-Identification
by: Li, Ziwen, et al.
Published: (2026)

Semantic-Preserving Adversarial Attacks on LLMs: An Adaptive Greedy Binary Search Approach
by: Zhang, Chong, et al.
Published: (2025)

Efficient and Stealthy Jailbreak Attacks via Adversarial Prompt Distillation from LLMs to SLMs
by: Li, Xiang, et al.
Published: (2025)

RTD-Guard: A Black-Box Textual Adversarial Detection Framework via Replacement Token Detection
by: Zhu, He, et al.
Published: (2026)

De-Anonymization at Scale via Tournament-Style Attribution
by: Zhang, Lirui, et al.
Published: (2026)

A Case Study on the Impact of Anonymization Along the RAG Pipeline
by: Bodea, Andreea-Elena, et al.
Published: (2026)

Data Extraction Attacks in Retrieval-Augmented Generation via Backdoors
by: Peng, Yuefeng, et al.
Published: (2024)

Fight Poison with Poison: Enhancing Robustness in Few-shot Machine-Generated Text Detection with Adversarial Training
by: Duan, Wenjing, et al.
Published: (2026)

Towards the Anonymization of the Language Modeling
by: Boutet, Antoine, et al.
Published: (2025)

Are You Getting What You Pay For? Auditing Model Substitution in LLM APIs
by: Cai, Will, et al.
Published: (2025)

Mask-GCG: Are All Tokens in Adversarial Suffixes Necessary for Jailbreak Attacks?
by: Mu, Junjie, et al.
Published: (2025)

Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models
by: Wei, Zhang, et al.
Published: (2025)

You Only Anonymize What Is Not Intent-Relevant: Suppressing Non-Intent Privacy Evidence
by: Shen, Weihao, et al.
Published: (2026)

You Can Run But You Can't Hide: Runtime Protection Against Malicious Package Updates For Node.js
by: Ohm, Marc, et al.
Published: (2023)

Adversarial Decoding: Generating Readable Documents for Adversarial Objectives
by: Zhang, Collin, et al.
Published: (2024)

Safely Learning with Private Data: A Federated Learning Framework for Large Language Model
by: Zheng, JiaYing, et al.
Published: (2024)

Demo: TOSense -- What Did You Just Agree to?
by: Chen, Xinzhang, et al.
Published: (2025)

Anonymous YARA Rules Are Not Anonymous
by: Isah, Usman Rabiu, et al.
Published: (2026)

Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks
by: Zhang, Xinyu, et al.
Published: (2023)

Adversarial Robustness through Dynamic Ensemble Learning
by: Waghela, Hetvi, et al.
Published: (2024)

Adversarial Text Generation with Dynamic Contextual Perturbation
by: Waghela, Hetvi, et al.
Published: (2025)

Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals
by: Zheng, Rui, et al.
Published: (2024)

Iron Sharpens Iron: Defending Against Attacks in Machine-Generated Text Detection with Adversarial Training
by: Li, Yuanfan, et al.
Published: (2025)

"Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced Distillation
by: Liang, Zi, et al.
Published: (2024)

from Benign import Toxic: Jailbreaking the Language Model via Adversarial Metaphors
by: Yan, Yu, et al.
Published: (2025)

SafeReview: Defending LLM-based Review Systems Against Adversarial Hidden Prompts
by: Xin, Yuan, et al.
Published: (2026)

Geometry-Aware Localized Watermarking for Copyright Protection in Embedding-as-a-Service
by: Chen, Zhimin, et al.
Published: (2026)

RAT-Bench: A Comprehensive Benchmark for Text Anonymization
by: Krčo, Nataša, et al.
Published: (2026)

Bergeron: Combating Adversarial Attacks through a Conscience-Based Alignment Framework
by: Pisano, Matthew, et al.
Published: (2023)

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

Automated Repeatable Adversary Threat Emulation with Effects Language (EL)
by: Damodaran, Suresh K., et al.
Published: (2025)

Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs
by: Liu, Fan, et al.
Published: (2024)

S-Eval: Towards Automated and Comprehensive Safety Evaluation for Large Language Models
by: Yuan, Xiaohan, et al.
Published: (2024)

Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack
by: Zhou, Ying, et al.
Published: (2024)

PRISM: Privacy-Aware Routing for Adaptive Cloud-Edge LLM Inference via Semantic Sketch Collaboration
by: Zhan, Junfei, et al.
Published: (2025)

The Landscape of Prompt Injection Threats in LLM Agents: From Taxonomy to Analysis
by: Wang, Peiran, et al.
Published: (2026)

I still know it's you! On Challenges in Anonymizing Source Code
by: Horlboge, Micha, et al.
Published: (2022)

When RAG Chatbots Expose Their Backend: An Anonymized Case Study of Privacy and Security Risks in Patient-Facing Medical AI
by: Madrid-García, Alfredo, et al.
Published: (2026)