Enterprise Market Volatility Predictions through Synthetic DNA and Mutant Nucleotides

    公开(公告)号:US20220383136A1

    公开(公告)日:2022-12-01

    申请号:US17334191

    申请日:2021-05-28

    IPC分类号: G06N3/12 G06Q30/02

    摘要: Aspects of the disclosure relate to using synthetic DNA stranding and mutant nucleotide processes to conduct enterprise market volatility predictions. In some embodiments, a computing platform may receive raw market data from a plurality of lines of business of an enterprise organization. Thereafter, the computing platform may preprocess the raw market data to obtain enterprise level market data, execute synthetic DNA stranding of the enterprise level market data to obtain synthetic DNA stranded market data, run the synthetic DNA stranded market data through one or more market volatility models, and compile results from the market volatility models on the synthetic DNA stranded market data. The computing platform may transmit results from the market volatility models on the synthetic DNA stranded market data. The transmitted results may be configured to display a market application interface that includes market volatility forecasting parameters based on results of the market volatility models.

    Application resiliency via context aware scriptless auditing equilibrium

    公开(公告)号:US11422927B1

    公开(公告)日:2022-08-23

    申请号:US17338851

    申请日:2021-06-04

    IPC分类号: G06F11/36

    摘要: Systems, computer program products, and methods are described herein for testing application resiliency via context aware auditing equilibrium. The present invention is configured to receive an indication to test application resiliency of an application; initiate a resiliency test engine on the application; determine, using the resiliency test engine, one or more artifacts associated with the application to be tested; determine a first subset of the one or more test scripts is able to capture a behavior of a first subset of the one or more artifacts; initiate a context-based classification engine on the first subset of the one or more test scripts and the first subset of the one or more artifacts; classify the first subset of the one or more test scripts into a supporting behavior class and an opposing behavior class; generate a graphical representation of the classification; and display the graphical representation of the classification.