Visualized Penetration Testing (VPEN)

    公开(公告)号:US20210344703A1

    公开(公告)日:2021-11-04

    申请号:US16864869

    申请日:2020-05-01

    Abstract: A method is disclosed for enhanced enumeration of network exploits, the method including scanning a network to identify and enumerate vulnerability exploit data from network scan results; accessing a vulnerability database to compare the vulnerability exploit data with stored vulnerability data and, and in response to identifying a match between the vulnerability exploit data and the stored vulnerability data, creating enhanced vulnerability exploit data; organizing the enhanced vulnerability exploit data in a hierarchal tree, table, or other format for display on a computer graphical user interface (GUI) or as input to a computerized system for processing; and updating the vulnerability database with the enhanced vulnerability exploit data.

    SYSTEM AND METHOD FOR DIGITAL STEGANOGRAPHY PURIFICATION

    公开(公告)号:US20210192019A1

    公开(公告)日:2021-06-24

    申请号:US17123948

    申请日:2020-12-16

    Abstract: Exemplary systems and methods are disclosed for removing steganography from digital data is disclosed. The method and system involve receiving a digital data. At least one processing device accesses a steganography purifier model. The at least one processing device includes at least a generator configured to scale a magnitude of individual data elements of the digital data from a first value range to a second value range. The scaled data elements are downsampled to remove steganography data embedded in the digital data and produce a purified version. The purified version is upsampled by interpolating new data elements between one or more adjacent data elements to provide an upsampled purified version. The magnitude of the data elements of the upsampled purified version are scaled from the second value range to the first value range to generate a purified output version.

    SYSTEM AND METHOD FOR DIGITAL IMAGE STEGANOGRAPHY DETECTION USING AN ENSEMBLE OF NEURAL SPATIAL RICH MODELS

    公开(公告)号:US20210150312A1

    公开(公告)日:2021-05-20

    申请号:US17098037

    申请日:2020-11-13

    Abstract: Exemplary systems and methods are disclosed for detecting embedded data in a digital image. The system includes a processing device that extracts one or more features from a digital image and analyzes the one or more extracted features in a plurality of steganography analyzers, each steganography analyzer configured to execute a different steganography algorithm. The processing device generates an output data value at each steganography analyzer, the output data value indicating a probability that the digital image includes steganography according to the steganography algorithm of the steganography analyzer. Each output probability value is fed to an ensemble classifier, the ensemble classifier including a neural network in which the output probability values of the plurality of steganography analyzers are ensembled together to generate an output ensemble data value indicating a probability that the digital image includes any steganography according to the steganography algorithms of the steganography analyzers.

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