USING MACHINE-LEARNING MODELS TO DETERMINE GRADUATED LEVELS OF ACCESS TO SECURED DATA FOR REMOTE DEVICES

    公开(公告)号:US20230161887A1

    公开(公告)日:2023-05-25

    申请号:US17532002

    申请日:2021-11-22

    IPC分类号: G06F21/60 G06F21/31 G06F21/53

    摘要: Aspects of the disclosure relate to using machine-learning models to determine graduated levels of access to secured data for remote devices. In some embodiments, a computing platform may establish a connection with a mobile device. Subsequently, based on establishing the connection, the platform may identify initial device information, device features, and user information. The platform may input the identified information into an authentication model to compute a baseline authentication score and then may identify an initial level of access to secured resources for the mobile device. Thereafter, the platform may receive from the mobile device, AR/VR device information captured by the mobile device. The platform may input the AR/VR device information into the authentication model to compute an augmented authentication score. Based on the augmented score, the platform may identify an augmented level of access to secured resources for the mobile device.

    Recursive Data and Electronic Signature Document Updater

    公开(公告)号:US20230145722A1

    公开(公告)日:2023-05-11

    申请号:US17523278

    申请日:2021-11-10

    摘要: Aspects of the disclosure relate to computing hardware and software for performing uniform document updates. A computing platform may receive, from a user device, a document change request. The computing platform may authenticate authority of a user of the user device to perform the document change request. Based on authenticating the authority of the user of the user device to perform the document change request, the computing platform may identify storage locations at which documents that are affected by the document change request are located. The computing platform may access the documents at each of the storage locations. The computing platform may scan the documents to identify locations, within the documents, of changes to be made, which may include identifying the locations based on enterprise-adopted change tags. The computing platform may write the changes to the documents at the identified locations based on the enterprise-adopted change tags.

    System and Method for Efficient Transliteration of Machine Interpretable Languages

    公开(公告)号:US20230129782A1

    公开(公告)日:2023-04-27

    申请号:US17557456

    申请日:2021-12-21

    IPC分类号: G06F16/248 G06F16/2453

    摘要: Aspects of the disclosure relate to transliteration of machine interpretable languages. A computing platform may configure a client application to use a custom driver when communicating with an enterprise database. The computing platform may receive a database query formatted in a first database format corresponding to a first database. The computing platform may translate, using a query translation library, the database query from the first database format into a second database format corresponding to a second database, which may cause the custom driver to execute a transliteration process using pre-verified query keys stored in the query translation library to convert the database query from the first database format into the second database format. The computing platform may execute the translated database query on the second database to obtain a query result, and may send the query result to the client application.

    System to correct model drift for natural language understanding

    公开(公告)号:US11562137B2

    公开(公告)日:2023-01-24

    申请号:US16847895

    申请日:2020-04-14

    摘要: A system retrains a natural language understanding (NLU) model by regularly analyzing electronic documents including web publications such as online newspapers, blogs, social media posts, etc. to understand how word and phrase usage is evolving. Generally, the system determines the frequency of words and phrases in the electronic documents and updates an NLU dictionary depending on whether certain words or phrases are being used more frequently or less frequently. This dictionary is then used to retrain the NLU model, which is then applied to predict the meaning of text or speech communicated by a people group. By analyzing electronic documents such as web publications, the system is able to stay up-to-date on the vocabulary of the people group and make correct predictions as the vocabulary changes (e.g., due to natural disaster). In this manner, the safety of the people is improved.

    MULTI-LAYER NEURAL NETWORK AND CONVOLUTIONAL NEURAL NETWORK FOR CONTEXT SENSITIVE OPTICAL CHARACTER RECOGNITION

    公开(公告)号:US20230019919A1

    公开(公告)日:2023-01-19

    申请号:US17375319

    申请日:2021-07-14

    发明人: Maharaj Mukherjee

    摘要: Aspects of the disclosure relate to OCR. A computing platform may train, using historical images, a CNN and a RNN to perform OCR/identify characters in context. The computing platform may receive an image of a document, and may input the image into the CNN, which may cause the CNN to output OCR information for the image and a confidence score. Based on identifying that the confidence score exceeds a confidence threshold, the computing platform may store the OCR information to enable subsequent access of a digital version of the document. Based on identifying that the confidence score does not exceed the confidence threshold, the computing platform may: 1) input the OCR information into the first RNN, which may cause the first RNN to output contextual OCR information for the image, and 2) store the contextual OCR information to enable subsequent access of the digital version of the document.

    Recommendation Engine Accounting for Preference Drift

    公开(公告)号:US20220414739A1

    公开(公告)日:2022-12-29

    申请号:US17359966

    申请日:2021-06-28

    发明人: Maharaj Mukherjee

    摘要: Aspects of the disclosure relate to content prediction. A computing platform may train a collaborative recommendation engine to output recommendation information based on historical preference information and corresponding data drift. The computing platform may receive an account access request from a user device. The computing platform may identify, at a first time and using the collaborative recommendation engine, a preference group for the user device. The computing platform may receive, at a second time later than the first time, a second account access request from the user device. The computing platform may identify, using the collaborative recommendation engine, the preference group and data drift corresponding to the preference group between the first time and the second time, which may indicate a second set of preferences at the second time. The computing platform may generate, based on the second set of preferences, recommendation information for the user device.

    INFORMATION SECURITY SYSTEM AND METHOD FOR MACHINE-TO-MACHINE (M2M) SECURITY AND VALIDATION

    公开(公告)号:US20220377067A1

    公开(公告)日:2022-11-24

    申请号:US17324165

    申请日:2021-05-19

    IPC分类号: H04L29/06

    摘要: A system for implementing Machine-to-Machine (M2M) validation receives a request from a unrecognized computing device to establish a communication with a first trusted computing device. The first trusted computing device sends a query message to a second trusted computing device to determine whether the unrecognized computing device is in a list of trusted devices associated with the second trusted computing device. The first trusted computing device receives a response message from the second trusted computing device indicating that the unrecognized computing device is in the list of trusted devices. In response, to receiving the response message, the first trusted computing device approves the request of the unrecognized computing device.

    EVENT MANAGEMENT AND VALIDATION PLATFORM USING A RECURSIVE HIERARCHIC BLOCKCHAIN

    公开(公告)号:US20220335525A1

    公开(公告)日:2022-10-20

    申请号:US17853994

    申请日:2022-06-30

    发明人: Maharaj Mukherjee

    摘要: Aspects of the disclosure relate to implementation of a recursive hierarchic blockchain for event validation and processing. A computing platform may receive event data from first and second data sources. The computing platform may store, in a first distributed ledger, an event record for each event from the first data source and may store, in a second distributed ledger, an event record for each event from both data sources. In response to determining that a validation condition for a current block of the second distributed ledger has been satisfied, the computing platform may compute a hash and generate a numeric representation of the first distributed ledger. In a new block of the second distributed ledger, the computing platform may store the hash and the numeric representation. The computing platform may write, to the new block of the second distributed ledger, additional event data from both data sources.

    System and method for automatic video categorization

    公开(公告)号:US11475668B2

    公开(公告)日:2022-10-18

    申请号:US17066631

    申请日:2020-10-09

    摘要: An apparatus includes a memory and processor. The memory stores a set of object categories and a set of motion categories. The processor splits a video into an ordered series of frames. For each frame, the processor determines that the frame includes an image of an object of a given object category. The processor assigns the given object category to the frame and stores the assigned object category in an ordered series of object category assignments. The processor determines, based on a subset of the ordered series of object category assignments, that the video used to generate the ordered series of object category assignments depicts a motion of a given motion category. The processor assigns the given motion category to the video.