Safety, Security, and Cognitive Risks in World Models
2026-04-03T07:23:38Z•abd7f3a137bbeaef104b8e36f9a316e27e03bdcf53d0de3460b243d957c17196
AI-assisted-verificationAssertainCWE-mappingEXHIB-benchmarkFoodGuard-4BFoodGuardBenchLLM-safetyNVDLA-case-studyRefinementEngineSelfGraderadversarial-attacksattacker-taxonomyautomated-assertionsbinary-function-similaritycyclic-Laplacedifferential-privacyfood-safetyguardrailshardware-securityjailbreak-detectionpolicy-deployment','network-enforcement','CTI-integration','façprivate-countsrepresentational-risktrajectory-persistenceworld-models
What happened
This collection aggregates 10 recent security- and safety-focused CS papers (arXiv, 2026-04-03) covering risks, benchmarks, and defenses across AI, hardware, privacy, and software supply chains. Key contributions include: (1) a survey of safety, security, and cognitive risks from learned world models with formal definitions (trajectory persistence, representational risk), an attacker-capability taxonomy, a unified threat model, and empirical trajectory-persistent adversarial attacks; (2) qualitative research on surveillance, censorship, and privacy harms from in-prison digital devices with UX-
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- abd7f3a137bbeaef104b8e36f9a316e27e03bdcf53d0de3460b243d957c17196
- Enrichment time
- 2026-04-03T07:23:38Z
- AI-assisted enrichment
- Yes
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