{"data":{"id":"ab9b39a7-4ecb-40b4-bb77-151748fa78be","title":"Learning Personalized Human Decision Models in Cyber Defense","summary":"Researchers propose a kernel-based inverse learning framework that infers user-specific latent cognitive traits, such as risk tolerance, curiosity, and prospect, from limited behavioral data, modeling human decisions as a Markov decision process. They validated it with a psychological survey of 108 participants in the TTCP CAGE Challenge 2 testbed, finding it accurately recovers individualized traits and predicts behavior well even with sparse data and behavioral variability.","solution":"N/A -- no mitigation discussed in source.","labels":["research","industry"],"sourceUrl":"http://ieeexplore.ieee.org/document/11277371","publishedAt":"2025-12-04T13:17:12.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2025-12-04T13:17:12.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"agent","llmSpecific":false,"classifierConfidence":0.7,"researchCategory":"peer_reviewed","atlasIds":null}}