Netskope had five patents in artificial intelligence during Q1 2024. Netskope Inc’s patents filed in Q1 2024 focus on technologies for intercepting and analyzing webpages to detect phishing attacks, performing multi-label SVM classification of documents, training classifiers to classify files as encrypted or not, and facilitating User and Entity Behavior Analytics (UEBA) by monitoring file movements and detecting encryption. These technologies aim to enhance cybersecurity measures and protect against data exfiltration and unauthorized file transfers. GlobalData’s report on Netskope gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Netskope grant share with artificial intelligence as a theme is 20% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Metadata-based detection and prevention of phishing attacks (Patent ID: US20240073245A1)
The technology disclosed in this patent involves a computer-implemented method for detecting and preventing phishing attacks by intercepting webpages rendered by servers in response to user actions, analyzing images and fields on the webpage to identify hosted services and confidential information, intercepting requests for confidential information, and determining if the information is being exfiltrated to an unsanctioned resource. If a phishing attack is detected, the technology blocks the transmission of confidential information to the unsanctioned resource. The method also involves analyzing requests, identifying sanctioned resource addresses, and performing security actions based on a security policy.
Additionally, the patent includes claims for a security system that implements the method described above. The system includes processors and memory storing instructions for intercepting webpages, analyzing images and fields, intercepting requests, identifying resource addresses, and performing security actions. The system also includes a metadata store for sanctioned resource addresses, a convolutional neural network for mapping webpage images to hosted services, and instructions for analyzing requests, performing security actions, and analyzing fields on webpages. The system is designed to effectively detect and prevent phishing attacks by analyzing and responding to user interactions with webpages.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
