ADOBE had 12 patents in cybersecurity during Q1 2024. ADOBE Inc’s patents filed in Q1 2024 focus on enhancing document security and privacy. One patent involves filling digital documents using user identity models of client devices, while another patent utilizes machine learning models to prevent inadvertent disclosure of sensitive data by identifying entities associated with private information and computing a privacy score to indicate potential exposure. The interface is updated to distinguish and modify target portions of unstructured text data to mitigate privacy risks. GlobalData’s report on ADOBE gives a 360-degree view of the company including its patenting strategy. Buy the report here.

ADOBE grant share with cybersecurity as a theme is 25% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Filling digital documents using multi-tiered user identity models based on decentralized identity (Patent ID: US20240056309A1)

The patent filed by ADOBE Inc. describes a system, method, and computer-readable media for filling in digital documents using user identity models of client devices. The system receives a digital document with a fillable field, retrieves a decentralized identity credential for the client device associated with the document, and modifies the document by filling in the field using the user attribute from the credential. The method involves verifying user attributes, generating privacy-preserving arguments for sensitive information, and interacting with multiple client devices for verification.

The patent also covers the retrieval of verifiable credentials from multi-tier user identity models, submitting requests for additional decentralized identity credentials, and utilizing fuzzy matching algorithms for determining attribute correspondence. The system provides verification indications on the graphical user interface, allows user interactions for editing fillable fields, and ensures privacy by using privacy-preserving arguments. Additionally, the system can modify additional fillable fields based on user interactions, enhancing the overall user experience with digital document filling.

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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.