公开(公告)号：US20210192019A1

公开(公告)日：2021-06-24

申请号：US17123948

申请日：2020-12-16

Applicant: Booz Allen Hamilton Inc.

Inventor： Jonathan Richard LWOWSKI ,  Isaac Alexander CORLEY

IPC: G06F21/16 ,  G06T3/40 ,  G10L25/57 ,  G10L19/02

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.

公开(公告)号：US20210150312A1

公开(公告)日：2021-05-20

申请号：US17098037

申请日：2020-11-13

Applicant: Booz Allen Hamilton Inc.

Inventor： Jonathan Richard LWOWSKI ,  Isaac Alexander CORLEY

IPC: G06N3/04 ,  G06T1/00 ,  G06K9/62

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.