:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Ren, Junyu, Pan, Xingjian, Gan, Wensheng, Yu, Philip S.
Formato:	Preprint
Publicado:	2026
Materias:	Cryptography and Security
Acceso en línea:	https://arxiv.org/abs/2604.12548
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Digital Fingerprinting on Multimedia: A Survey
por: Chen, Wendi, et al.
Publicado: (2024)

AgentVisor: Defending LLM Agents Against Prompt Injection via Semantic Virtualization
por: Ying, Zonghao, et al.
Publicado: (2026)

Defending Against Prompt Injection with DataFilter
por: Wang, Yizhu, et al.
Publicado: (2025)

WARD: Adversarially Robust Defense of Web Agents Against Prompt Injections
por: Cao, Tri, et al.
Publicado: (2026)

Towards Understanding the Safety Boundaries of DeepSeek Models: Evaluation and Findings
por: Ying, Zonghao, et al.
Publicado: (2025)

SoK: A Comprehensive Security Analysis of Jailbreak Resilience in GPT and DeepSeek Models
por: Wu, Xiaodong, et al.
Publicado: (2025)

Defending Against Prompt Injection With a Few DefensiveTokens
por: Chen, Sizhe, et al.
Publicado: (2025)

Defense Against Prompt Injection Attack by Leveraging Attack Techniques
por: Chen, Yulin, et al.
Publicado: (2024)

StruQ: Defending Against Prompt Injection with Structured Queries
por: Chen, Sizhe, et al.
Publicado: (2024)

Watermarking Techniques for Large Language Models: A Survey
por: Liang, Yuqing, et al.
Publicado: (2024)

PromptSleuth: Detecting Prompt Injection via Semantic Intent Invariance
por: Wang, Mengxiao, et al.
Publicado: (2025)

Strengthening Polymorphic Prompt Assembling: Dynamic Separator Generation Against Emerging Prompt Injection Attacks
por: Dorzhiev, Nima, et al.
Publicado: (2026)

To Protect the LLM Agent Against the Prompt Injection Attack with Polymorphic Prompt
por: Wang, Zhilong, et al.
Publicado: (2025)

ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection
por: Weng, Shihao, et al.
Publicado: (2026)

Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects
por: Rahman, Anichur, et al.
Publicado: (2025)

The dark deep side of DeepSeek: Fine-tuning attacks against the safety alignment of CoT-enabled models
por: Xu, Zhiyuan, et al.
Publicado: (2025)

Analysis of LLMs Against Prompt Injection and Jailbreak Attacks
por: Jaiswal, Piyush, et al.
Publicado: (2026)

Securing AI Agents Against Prompt Injection Attacks
por: Ramakrishnan, Badrinath, et al.
Publicado: (2025)

ASPI: Seeking Ambiguity Clarification Amplifies Prompt Injection Vulnerability in LLM Agents
por: Sehwag, Udari Madhushani, et al.
Publicado: (2026)

R1dacted: Investigating Local Censorship in DeepSeek's R1 Language Model
por: Naseh, Ali, et al.
Publicado: (2025)

Prompt Control-Flow Integrity: A Priority-Aware Runtime Defense Against Prompt Injection in LLM Systems
por: Alam, Md Takrim Ul, et al.
Publicado: (2026)

AegisAgent: An Autonomous Defense Agent Against Prompt Injection Attacks in LLM-HARs
por: Wang, Yihan, et al.
Publicado: (2025)

Attention is All You Need to Defend Against Indirect Prompt Injection Attacks in LLMs
por: Zhong, Yinan, et al.
Publicado: (2025)

SecAlign: Defending Against Prompt Injection with Preference Optimization
por: Chen, Sizhe, et al.
Publicado: (2024)

Lessons from Defending Gemini Against Indirect Prompt Injections
por: Shi, Chongyang, et al.
Publicado: (2025)

Is Your Prompt Safe? Investigating Prompt Injection Attacks Against Open-Source LLMs
por: Wang, Jiawen, et al.
Publicado: (2025)

LogJack: Indirect Prompt Injection Through Cloud Logs Against LLM Debugging Agents
por: Shah, Harsh
Publicado: (2026)

Prompt Injection Attack to Tool Selection in LLM Agents
por: Shi, Jiawen, et al.
Publicado: (2025)

RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
por: Zhong, Peter Yong, et al.
Publicado: (2025)

WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks
por: Evtimov, Ivan, et al.
Publicado: (2025)

VortexPIA: Indirect Prompt Injection Attack against LLMs for Efficient Extraction of User Privacy
por: Cui, Yu, et al.
Publicado: (2025)

The Vulnerability of LLM Rankers to Prompt Injection Attacks
por: Yin, Yu, et al.
Publicado: (2026)

PROMPTFUZZ: Harnessing Fuzzing Techniques for Robust Testing of Prompt Injection in LLMs
por: Yu, Jiahao, et al.
Publicado: (2024)

A Novel Evaluation Framework for Assessing Resilience Against Prompt Injection Attacks in Large Language Models
por: Yip, Daniel Wankit, et al.
Publicado: (2024)

Defending Against Indirect Prompt Injection Attacks With Spotlighting
por: Hines, Keegan, et al.
Publicado: (2024)

Node Injection Attack Based on Label Propagation Against Graph Neural Network
por: Zhu, Peican, et al.
Publicado: (2024)

LivePI: More Realistic Benchmarking of Agents Against Indirect Prompt Injection
por: Zhao, Lei, et al.
Publicado: (2026)

MELON: Provable Defense Against Indirect Prompt Injection Attacks in AI Agents
por: Zhu, Kaijie, et al.
Publicado: (2025)

A Multi-Agent LLM Defense Pipeline Against Prompt Injection Attacks
por: Hossain, S M Asif, et al.
Publicado: (2025)

Signed-Prompt: A New Approach to Prevent Prompt Injection Attacks Against LLM-Integrated Applications
por: Suo, Xuchen
Publicado: (2024)