Global Web, Local Privacy? An International Review of Web Tracking
2026-04-22T07:23:31Z•3db35ca8062433192aafe7cb0f14f9b8c4d50b737bed4f8db7ea66ee9fa7d614
Arbiter-KDEJAGDPRLLM-APIsLLM-tutorsRAGTEEs (SGX/SEV)ad-techadversarial-studentsagent-safetycopyrightdata-protectiondecision-tree-extractiongovernance-first-architectureinextractabilitylegal-compliancemachine-learning-securitymodel-extractionmodel-training-liabilityowner-harmprivacyside-channelsoft-failure-jammingtaint-trackingweb-tracking
What happened
This collection (arXiv feed) contains multiple security- and privacy-focused ML and systems papers with concrete attack discoveries, threat-model framing, new measurement tools, and defenses. Key findings include: a multi-country measurement showing EU privacy rules (GDPR/ePrivacy) materially reduce web tracking and cookie-banner interactions; a legal analysis arguing post-hoc mitigation (unlearning/guardrails) cannot retroactively absolve unlawful data acquisition during model training; Arbiter-K, a governance-first execution kernel/semantic ISA that enforces tainting and deterministic interd
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 3db35ca8062433192aafe7cb0f14f9b8c4d50b737bed4f8db7ea66ee9fa7d614
- Enrichment time
- 2026-04-22T07:23:31Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.