RAGShield: Provenance-Verified Defense-in-Depth Against Knowledge Base Poisoning in Government Retrieval-Augmented Generation Systems
RAGShield: Provenance-Verified Defense-in-Depth Against Knowledge Base Poisoning in Government Retrieval-Augmented Generation Systems explores RAGShield provides a five-layer defense-in-depth framework for government RAG systems, using supply chain provenance verification to prevent knowledge base poisoning attacks.. Commercial viability score: 7/10 in AI Security.
Updated 23 hours ago
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisTowards Secure Retrieval-Augmented Generation: A Comprehensive Review of Threats, Defenses and BenchmarksViability: 4.0
- Builds On ThisConnect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation SystemsViability: 5.0
- Builds On ThisKEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented GenerationViability: 4.0
- Builds On ThisPIDP-Attack: Combining Prompt Injection with Database Poisoning Attacks on Retrieval-Augmented Generation SystemsViability: 4.0
- Builds On ThisSupercharging Federated Intelligence Retrieval
Related Resources
- Why is AI security important?(question)
- What is the focus of AI security research?(question)
- How do AI security measures protect systems?(question)