Security in the Fine-Tuning Lifecycle of Large Language Models: Threats, Defenses,Evaluation, and Future Directions
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Wenjuan, Liu, Yitao, Chen, Runze, Buyya, Rajkumar |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions
by: Sai, Siva, et al.
Published: (2025)
by: Sai, Siva, et al.
Published: (2025)
Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices
by: Abdali, Sara, et al.
Published: (2024)
by: Abdali, Sara, et al.
Published: (2024)
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)
PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
by: Liu, Yi, et al.
Published: (2025)
by: Liu, Yi, et al.
Published: (2025)
Large Language Models Are Unreliable for Cyber Threat Intelligence
by: Mezzi, Emanuele, et al.
Published: (2025)
by: Mezzi, Emanuele, et al.
Published: (2025)
Evaluating Large Language Models for Security Bug Report Prediction
by: Soltaniani, Farnaz, et al.
Published: (2026)
by: Soltaniani, Farnaz, et al.
Published: (2026)
Acceptance Cards:A Four-Diagnostic Standard for Safe Fine-Tuning Defense Claims
by: Konrad, Phongsakon Mark, et al.
Published: (2026)
by: Konrad, Phongsakon Mark, et al.
Published: (2026)
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)
Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques
by: Jaffal, Niveen O., et al.
Published: (2025)
by: Jaffal, Niveen O., et al.
Published: (2025)
A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective
by: Yu, Lei, et al.
Published: (2024)
by: Yu, Lei, et al.
Published: (2024)
A Factored MDP Approach To Moving Target Defense With Dynamic Threat Modeling and Cost Efficiency
by: Bose, Megha, et al.
Published: (2024)
by: Bose, Megha, et al.
Published: (2024)
PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
by: Ertan, Murat Bilgehan, et al.
Published: (2026)
by: Ertan, Murat Bilgehan, et al.
Published: (2026)
Distributed Threat Intelligence at the Edge Devices: A Large Language Model-Driven Approach
by: Hasan, Syed Mhamudul, et al.
Published: (2024)
by: Hasan, Syed Mhamudul, et al.
Published: (2024)
Evaluating Prompt Injection Defenses for Educational LLM Tutors: Security-Usability-Latency Trade-offs
by: Maiorano, Alexandre Cristovão
Published: (2026)
by: Maiorano, Alexandre Cristovão
Published: (2026)
Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions -- A Systematic Review
by: Ali, Md Shahin, et al.
Published: (2024)
by: Ali, Md Shahin, et al.
Published: (2024)
CTINexus: Automatic Cyber Threat Intelligence Knowledge Graph Construction Using Large Language Models
by: Cheng, Yutong, et al.
Published: (2024)
by: Cheng, Yutong, et al.
Published: (2024)
SHIELD: Secure Hypernetworks for Incremental Expansion Learning Defense
by: Krukowski, Patryk, et al.
Published: (2025)
by: Krukowski, Patryk, et al.
Published: (2025)
The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks
by: Chen, Xiaoyi, et al.
Published: (2023)
by: Chen, Xiaoyi, et al.
Published: (2023)
Securing Healthcare with Deep Learning: A CNN-Based Model for medical IoT Threat Detection
by: Mohamadi, Alireza, et al.
Published: (2024)
by: Mohamadi, Alireza, et al.
Published: (2024)
Checkpoint-GCG: Auditing and Attacking Fine-Tuning-Based Prompt Injection Defenses
by: Yang, Xiaoxue, et al.
Published: (2025)
by: Yang, Xiaoxue, et al.
Published: (2025)
Federated Large Language Models: Feasibility, Robustness, Security and Future Directions
by: Jiang, Wenhao, et al.
Published: (2025)
by: Jiang, Wenhao, et al.
Published: (2025)
Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
by: Yichao, Wu, et al.
Published: (2025)
by: Yichao, Wu, et al.
Published: (2025)
Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
by: Liu, Guozhi, et al.
Published: (2025)
by: Liu, Guozhi, et al.
Published: (2025)
A Survey on Backdoor Threats in Large Language Models (LLMs): Attacks, Defenses, and Evaluations
by: Zhou, Yihe, et al.
Published: (2025)
by: Zhou, Yihe, et al.
Published: (2025)
Adversarial Text Purification: A Large Language Model Approach for Defense
by: Moraffah, Raha, et al.
Published: (2024)
by: Moraffah, Raha, et al.
Published: (2024)
LISAA: A Framework for Large Language Model Information Security Awareness Assessment
by: Cohen, Ofir, et al.
Published: (2024)
by: Cohen, Ofir, et al.
Published: (2024)
DP-Adam-AC: Privacy-preserving Fine-Tuning of Localizable Language Models Using Adam Optimization with Adaptive Clipping
by: Yang, Ruoxing
Published: (2025)
by: Yang, Ruoxing
Published: (2025)
Jailbreak Attacks and Defenses Against Large Language Models: A Survey
by: Yi, Sibo, et al.
Published: (2024)
by: Yi, Sibo, et al.
Published: (2024)
Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions
by: Hou, Xinyi, et al.
Published: (2025)
by: Hou, Xinyi, et al.
Published: (2025)
Security and Detectability Analysis of Unicode Text Watermarking Methods Against Large Language Models
by: Hellmeier, Malte
Published: (2025)
by: Hellmeier, Malte
Published: (2025)
Self-Mined Hardness for Safety Fine-Tuning
by: Gupta, Prakhar, et al.
Published: (2026)
by: Gupta, Prakhar, et al.
Published: (2026)
When Safety Geometry Collapses: Fine-Tuning Vulnerabilities in Agentic Guard Models
by: Hossain, Ismail, et al.
Published: (2026)
by: Hossain, Ismail, et al.
Published: (2026)
Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation
by: Li, Xianzhi, et al.
Published: (2024)
by: Li, Xianzhi, et al.
Published: (2024)
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
by: Lu, Ning, et al.
Published: (2025)
by: Lu, Ning, et al.
Published: (2025)
PoolFlip: A Multi-Agent Reinforcement Learning Security Environment for Cyber Defense
by: Cadet, Xavier, et al.
Published: (2025)
by: Cadet, Xavier, et al.
Published: (2025)
An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks
by: Boreiko, Valentyn, et al.
Published: (2024)
by: Boreiko, Valentyn, et al.
Published: (2024)
Securing Retrieval-Augmented Generation: A Taxonomy of Attacks, Defenses, and Future Directions
by: Xu, Yuming, et al.
Published: (2026)
by: Xu, Yuming, et al.
Published: (2026)
The Security Threat of Compressed Projectors in Large Vision-Language Models
by: Zhang, Yudong, et al.
Published: (2025)
by: Zhang, Yudong, et al.
Published: (2025)
Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness
by: Wang, Cheng-Long, et al.
Published: (2025)
by: Wang, Cheng-Long, et al.
Published: (2025)
Can Adversarial Code Comments Fool AI Security Reviewers -- Large-Scale Empirical Study of Comment-Based Attacks and Defenses Against LLM Code Analysis
by: Thornton, Scott
Published: (2026)
by: Thornton, Scott
Published: (2026)
Similar Items
-
Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions
by: Sai, Siva, et al.
Published: (2025) -
Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices
by: Abdali, Sara, et al.
Published: (2024) -
Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey
by: Huang, Tiansheng, et al.
Published: (2024) -
PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
by: Liu, Yi, et al.
Published: (2025) -
Large Language Models Are Unreliable for Cyber Threat Intelligence
by: Mezzi, Emanuele, et al.
Published: (2025)