{"data":{"id":"e922e890-1d97-4e61-abcd-b266df629021","title":"AdvScan: Black-Box Adversarial Example Detection at Runtime Through Power Analysis","summary":"AdvScan is a black-box method for detecting adversarial examples on TinyML models at runtime by analyzing power consumption. It builds a baseline of power signatures from benign inputs and applies a one-sample t-test to flag inputs whose signatures deviate significantly. Evaluated on three MLPerf Tiny models across two STM32 microcontrollers and 318,400 test inputs, it detected 99.984% of adversarial examples, with 40 false negatives and no false positives.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11386831","publishedAt":"2026-02-09T13:17:29.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_evasion"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["TinyML models","MLPerf Tiny benchmark models","STM32F303RC","STM32L562RE"],"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":"2026-02-09T13:17:29.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity","safety"],"aiComponentTargeted":"inference","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":"peer_reviewed","atlasIds":null}}