{"data":{"id":"5f9f9785-7b46-4e8e-839c-61b9939571de","title":"Efficient Prompt Security Detection for LLM Service Deployment in Edge-Cloud Networks","summary":"Large Language Models are vulnerable to prompt injection attacks (tricking an AI by hiding malicious instructions in its input), which poses security risks during deployment. This paper proposes BUUAS, a framework that uses Bayesian-inspired belief updates and a belief-weighted contextual multi-armed bandit mechanism (a decision-making approach that learns which security checks to prioritize) to detect prompt injection attacks more efficiently by focusing on high-risk user requests in edge-cloud networks (systems that process data both locally on edge devices and in remote data centers).","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11594973","publishedAt":"2026-07-03T13:23:36.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["prompt_injection"],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2026-07-03T13:23:36.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","safety"],"aiComponentTargeted":"inference","llmSpecific":true,"classifierConfidence":0.92,"researchCategory":"peer_reviewed","atlasIds":null}}