Defending LLMs Against Jailbreak Attacks
A Lightweight Token Distribution Approach for Enhanced Security
LightDefense offers a resource-efficient solution to protect Large Language Models from jailbreak attacks by strategically adjusting token probabilities.
- Shifts token distribution to prioritize safety disclaimers without additional model training
- Targets white-box models with a safety-oriented approach to vocabulary management
- Maintains model functionality while significantly improving defense against harmful prompts
- Reduces dependency on extensive data collection or auxiliary models
This research provides security teams with a practical, implementable defense mechanism that can be deployed to protect AI systems without compromising performance or requiring substantial resources.