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Update AirGap.md
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hamid58b authored May 21, 2024
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- "by restricting the agent’s access to only the data necessary for a specific task"
- Demonstrates effectiveness against context hijacking attacks.

### Method
- Utilizes two LLMs: a data minimizer and a conversational model.
- Minimized data access based on user-defined context.

## Methods
- Proposed context hijacking attack targeting LLM-based agents.
- Developed AirGapAgent to mitigate context hijacking.
- Utilized two LLMs:
- **Data minimizer** to decide appropriate data to share.
- Conversational model for interactions with minimized data.
- Context is user-defined to prevent adversarial influence.

### Result
- AirGapAgent achieves up to 97% privacy protection.
- Maintains core functionality of agents.
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