{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11271958","patent":{"patent_number":"US-11271958","title":"Efficient unsupervised anomaly detection on homomorphically encrypted data","assignee":null,"inventors":[],"filing_date":"2019-09-20T00:00:00.000Z","publication_date":"2022-03-08T00:00:00.000Z","cpc_codes":["H04L","G06F","G06F","G06F","G06F","G06N","G06N","G06N","H04L"],"num_claims":20,"abstract":"Aspects of the present disclosure describe techniques for detecting anomalous data in an encrypted data set. An example method generally includes receiving a data set of encrypted data points. A tree data structure having a number of levels is generated for the data set. Each level of the tree data structure generally corresponds to a feature of the encrypted plurality of features, and each node in the tree data structure at a given level represents a probability distribution of a likelihood that each data point is less than or greater than a split value determined for a given feature. An encrypted data point is received for analysis, and anomaly score is calculated based on a probability identified for each of the plurality of encrypted features. Based on determining that the calculated anomaly score exceeds a threshold value, the encrypted data point is identified as potentially anomalous."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Efficient unsupervised anomaly detection on homomorphically encrypted data","description":"Aspects of the present disclosure describe techniques for detecting anomalous data in an encrypted data set. An example method generally includes receiving a data set of encrypted data points. A tree ","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11271958","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11271958","citation_suggestion":"Patentable. \"Efficient unsupervised anomaly detection on homomorphically encrypted data\" (US-11271958). https://patentable.app/patents/US-11271958","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11271958","json":"https://patentable.app/api/llm-context/US-11271958","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T06:32:20.491Z"}