CSF: Black-box Fingerprinting via Compositional Semantics for Text-to-Image Models
2026-04-21T07:23:31Z•22720f4574794402b8b8f9bf33413e52c8eceba0fe73f04c27a3f9ed9a83cc51
PIIagent-protocolsblack-box-attributionblockchaincashback-double-dipconsent-modelcumulative-PII-exposuredata-availabilityfinancial-fraudintellectual-propertylight-clientslocalized-guardrailsmachine-learning-securitymemory-governancemnemonic-sovereigntymodel-extractionmulti-turn-LLMpolynomial-multiproofsprivacy-protectionreward-abusespectral-adversarial-attacksstate-space-modelsstateful-backdoorstext-to-image-fingerprinting
What happened
This feed contains multiple new security-relevant ML, financial, privacy, and blockchain papers. Key items: (1) CSF: a practical black‑box compositional semantic fingerprinting method to attribute fine‑tuned text‑to‑image models via rare prompt compositions (IP/provenance tool for API‑only models). (2) A systematic threat analysis of state‑space models (SSMs) that defines an SSM attack surface and introduces three novel attacks — spectral adversarial attacks, delayed‑trigger stateful backdoors, and state capacity saturation — with empirical validation in safety‑critical domains (genomics, clin
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 22720f4574794402b8b8f9bf33413e52c8eceba0fe73f04c27a3f9ed9a83cc51
- Enrichment time
- 2026-04-21T07:23:31Z
- AI-assisted enrichment
- Yes
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