System and method for digital steganography purification
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.
1. A system for removing steganography from a digital data, the system comprising:
a receiving device configured to receive digital data including at least one of image data and audio data; and
at least one processing device configured to access a steganography purifier model having 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, downsample the scaled data elements to remove steganography data embedded in the digital data and produce a purified version of the digital data, upsample the purified version of the digital data by interpolating new data elements between one or more adjacent data elements to provide an upsampled purified version of the digital data, and scale the data elements of the upsampled purified version of the digital data from the second value range to the first value range to generate a purified output version of the received digital data.
2. The system according to claim 1 , wherein the received digital data includes image data and the individual elements of the digital data are pixels.
3. The system according to claim 2 , wherein if the image data includes video image data, the system comprising:
a front-end device configured to parse the video image into a plurality of image frames and feed each image frame to the at least one processing device as the digital data.
4. The system according to claim 2 , wherein the magnitude of the individual data elements are scaled from a first value within the first value range of 0 to 255 to a second value within the second value range of 0 to 1.
5. The system according to claim 1 , wherein the received digital data includes audio data.
6. The system according to claim 5 , comprising:
a front-end device configured to reshape a vector of the audio data into a matrix format and feed the matrix to the at least one processor as the digital data.
7. The system according to claim 6 , wherein each individual element of the digital data is a sample of the audio data.
8. The system according to claim 6 , wherein the at least one processor is configured to generate the purified image as a matrix and reshape the matrix into a vector to generate purified audio data.
9. The system according to claim 1 , wherein steganography purifier model of the at least one processing device includes a discriminator configured to distinguish between the purified image generated by the generator and a cover image of the digital data during a training mode.
10. A method for removing steganography from digital data, comprising:
receiving, in a receiving device digital data including at least one of image data and audio data;
scaling, in at least one processing device which having an encoder of a steganography purifier model, a magnitude of individual data elements of the digital data from a first value range to a second value range;
downsampling, in the encoder architecture of the at least one processing device, the scaled data elements to remove steganography data embedded in the digital data and produce a purified version of the digital data;
upsampling, in the at least one processing device having a decoder of a steganography purifier model, the purified version of the digital data by interpolating new data elements between one or more adjacent data elements to provide an upsampled purified version of the digital data; and
scaling, in the decoder architecture of the at least one processing device, the data elements of the upsampled purified version of the digital data from the second value range to the first value range to generate a purified output version of the received digital data.
11. The method according to claim 10 , wherein if the image data includes a video image data, the method comprises:
parsing, in a front end device, the video image into a plurality of image frames; and
feeding each image frame to the at least one processing device as a digital data.
12. The method according to claim 11 , wherein if the received digital data includes audio data, the method comprises:
reshaping, in a front-end device, a vector of the audio data to a matrix format, and
feeding the matrix to the at least one processing device as the digital data.
13. The method according to claim 12 , wherein the purified output version of the received digital data is generated as a matrix of values, the method comprising:
reshaping the matrix into a vector to generate purified audio data.
14. The method according to claim 13 , wherein the digital data is received in a data signal and formatted according to an application program interface.
15. The method according to claim 10 , wherein scaling a magnitude of individual data elements of the digital dataset from a first value range to a second value range, comprises:
scaling the magnitude of the individual data elements from a first value within the first value range of 0 to 255 to a second value within the second value range of 0 to 1.
16. A method of training a system for removing steganography from digital data, the system having a receiving device and at least one processing device accessing a steganography purifier model having at least a generator for generating purified digital data and a discriminator for distinguishing between the purified digital data and cover data, the method comprising:
receiving, in the receiving device, a plurality of digital datasets including steganography, each digital datasets including one of image data and audio data;
scaling, via the generator of the at least one processing device, a magnitude of individual data elements of the digital dataset from a first value range to a second value range;
downsampling, via the generator of the at least one processing device, the digital dataset with the scaled elements to remove steganography data embedded in the digital data and producing a purified version of the digital dataset;
upsampling, via the generator of the at least one processing device, the purified version of the digital dataset by interpolating data between one or more adjacent data elements to provide an upsampled purified version of the digital dataset;
scaling, via the generator of the at least one processing device, the data elements of the upsampled purified version from the second value range to the first value range to generate a purified output version of the received digital dataset;
receiving, in the discriminator of the at least one processing device, the purified output version of the received digital dataset and a reference digital dataset, which corresponds to the digital dataset received by the receiving device; and
determining, via the discriminator of the at least one processing device, which of the purified version of the received digital dataset and the reference digital dataset contained steganography.
17. The method according to claim 16 , comprising:
feeding a determination result of the discriminator to the generator.
18. The method according to claim 17 , comprising:
wherein the nodal weights of the generator are adjusted so that a subsequent purified digital dataset has less steganographic content than a previous purified digital dataset.
19. The method according to claim 16 , comprising:
adjusting one or more nodal weights of the generator based on whether the determination result of the discriminator is correct.
20. The method according to claim 16 , wherein if the image data includes video image data, the method comprises:
parsing, in a front end device, the video image into a plurality of image frames; and
feeding each image frame to the at least one processing device as a corresponding digital dataset.
21. The method according to claim 16 , wherein if the received digital dataset includes audio data, the method comprises:
reshaping, in a front-end device, a vector of the audio data to a matrix format, and
feeding the matrix to the at least one processing device as a corresponding digital dataset.
22. The method according to claim 16 , wherein the purified output version of the digital dataset is generated as a matrix of values, the method comprising:
reshaping the matrix into a vector to generate a purified version of the audio data.