When the Aggregator Cheats: Data-Free Backdoors in Federated LLM-based QA Systems
arXiv 2606.27511•9757ddec38a34519fbc68acb2d3c329a9a1711b110de683447cd77a670fbcebe
adversarial-examplesagentic-aiarchitectural-separationautomotivebackdoordeceptionfederated-learningflexraygradient-reconstructionhardware-benchmarkinghomomorphic-encryptionllmmitre-attackpower-analysisprivacyprivate-set-intersectionprompt-injectionre-identificationshared-embeddingtiming-attacktinymltransparency-log
Paper metadata
- arXiv ID
- 2606.27511
- Version
- Not specified by this published record
- Category
- Computer Science — Cryptography and Security (cs.CR)
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Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 9757ddec38a34519fbc68acb2d3c329a9a1711b110de683447cd77a670fbcebe
- Enrichment time
- 2026-06-29T07:23:35Z
- AI-assisted enrichment
- Yes
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