{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11943200","patent":{"patent_number":"US-11943200","title":"Systems and methods for detecting anomalous virtual private network sessions using machine learning","assignee":null,"inventors":[],"filing_date":"2021-03-16T00:00:00.000Z","publication_date":"2024-03-26T00:00:00.000Z","cpc_codes":["G06N","H04L","G06N","G06N","H04L","H04L","H04L","H04L","H04L"],"num_claims":20,"abstract":"A virtual private network (VPN) security system obtains data regarding a VPN session including (i) for each of a plurality of first subnets, a number of allowed connection attempts by a computer system to that first subnet, (ii) for each of a plurality of second subnets, a number of blocked connection attempts by the computer system to that second subnet, (iii) for each of a plurality of first network ports, a number of allowed connection attempts by the computer system using that first network port, and (iv) for each of a plurality of second network ports, a number of blocked connection attempts by the computer system using that second network port. The security system determines, using a neural network, a metric representing an estimated likelihood that the VPN session is associated with a malicious activity, and controls the VPN session based on the metric."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Systems and methods for detecting anomalous virtual private network sessions using machine learning","description":"A virtual private network (VPN) security system obtains data regarding a VPN session including (i) for each of a plurality of first subnets, a number of allowed connection attempts by a computer syste","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11943200","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-11943200","citation_suggestion":"Patentable. \"Systems and methods for detecting anomalous virtual private network sessions using machine learning\" (US-11943200). https://patentable.app/patents/US-11943200","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11943200","json":"https://patentable.app/api/llm-context/US-11943200","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T15:08:57.148Z"}