Decentralized autonomous organization and blockchain-based incentivization framework for community-based facilities management
2026-05-20T07:23:33Z•fc97e9d192e4fe32a1654ea3c7fd3048d4aa0de44559fe47f6c1f4f6ebb5ddcd
adversarial-mlbackdoor-detectionblockchaindaodata-free-detectionfalse-data-injectionfinancial-fraudinfrastructure-securitylatent-space-defensellm-weaponizationmodel-auditingmultimodal-jailbreakpower-grid-securityprompt-injectionzero-trust
What happened
This collection of recent research highlights several high-impact AI and infrastructure security developments. DarkLLM demonstrates LLM-driven translation of natural-language attack instructions into transferable visual adversarial perturbations that successfully evade and manipulate foundation models (CLIP, SAM, frontier LLMs). GenAI-FDIA shows physics-informed generative models can synthesize highly stealthy false data injection attacks against power-system state estimation (evasion up to 100% after harmoniser fixes), revealing critical risks to grid integrity. Multiple works (DFBScanner, HT
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- fc97e9d192e4fe32a1654ea3c7fd3048d4aa0de44559fe47f6c1f4f6ebb5ddcd
- Enrichment time
- 2026-05-20T07:23:33Z
- AI-assisted enrichment
- Yes
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