{"data":{"id":"d19ac2b0-6e70-4701-a066-226d79b8469e","title":"EncFormer: Secure and Efficient Transformer Inference Over Encrypted Data","summary":"EncFormer addresses privacy concerns when machine-learning-as-a-service (MLaaS, where AI models run on remote servers) processes sensitive user data by enabling Transformer inference (running a type of AI model) over encrypted data. The system combines fully homomorphic encryption (FHE, allowing computation on encrypted data without decryption) and secure multiparty computation (MPC, where multiple parties jointly compute results without revealing their individual inputs) more efficiently than previous approaches, achieving significant improvements in speed and communication overhead while keeping data private.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11613199","publishedAt":"2026-07-17T13:20:09.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["OpenAI","Google"],"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":"2026-07-17T13:20:09.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["confidentiality"],"aiComponentTargeted":"inference","llmSpecific":true,"classifierConfidence":0.92,"researchCategory":"peer_reviewed","atlasIds":null}}