The disclosed computer-implemented method includes determining that audio quality is to be adjusted for a multimedia streaming connection over which audio data and video data are being streamed to a content player. The audio data is streamed at a specified audio quality level and the video data is streamed at a specified video quality level. The method also includes determining that a specified minimum video quality level is to be maintained while adjusting the audio quality level. Still further, the method includes dynamically adjusting the audio quality level of the multimedia streaming connection while maintaining the video quality level of the multimedia streaming connection at at least the specified minimum video quality level. Various other methods, systems, and computer-readable media are also disclosed.

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.

A method and computer programs for detecting document regions that will be excluded from a watermark embedding process are disclosed. The method comprises converting, by an adapter module, at least one page of a received document into a visual representation thereof, the visual representation keeping the position of the characters of the at least one page; receiving, by a text detector, the visual representation; processing, by the text detector, the visual representation using one or more artificial intelligence algorithms, and returning a list of invalid regions with their associated page positions as a result, wherein each invalid region of the list of invalid regions may have associated thereto a confidence score; and using, by a watermark embedding module or by a watermark extracting module, the list of invalid regions to provide a watermarked document or a message embedded in the document.

An information processing method for embedding watermark bits into weights of a first neural network includes: obtaining an output of a second neural network by inputting a plurality of input values obtained from a plurality of weights of the first neural network to the second neural network; obtaining second gradients of the respective plurality of input values based on an error between the output of the second neural network and the watermark bits; and updating the weights based on values obtained by adding first gradients of the weights of the first neural network that have been obtained based on backpropagation and the respective second gradients.

Methods, systems, and non-transitory computer readable storage media are disclosed for generating a machine-learning model and encoding ownership information in the machine-learning model. For example, the disclosed system can generate parameters of a machine-learning model utilizing digital content items modified by a filter. The disclosed system can then process digital content items modified by the filter to generate first outputs based on the digital content items being modified by the filter. The disclosed system can also process digital content items unmodified by the filter to generate second outputs based on the digital content items not being modified by the filter. The disclosed system can determine that the second outputs are degraded relative to the first outputs. Accordingly, the disclosed system can determine ownership of the machine-learning model based on detecting that information about the filter is embedded in parameters of the machine-learning model.

A data storage device and method for reliable watermarking are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to determine whether a watermarking operation to be performed on the data is to be performed by the controller or by the memory; in response to determining that the watermarking operation is to be performed by the controller, performing the watermarking operation; and in response to determining that the watermarking operation is to be performed by the memory, instruct the memory to perform the watermarking operation. Other embodiments are provided.

A computer system for the creation of subliminal image or watermarks where the apparent video is an “obvious” image and a subliminal or “clandestine” image or watermark is hidden within the data structure. The concept is envisioned for the cloaking of images, sound, video or like digitized non-coded information. The cloaked files may be intended for storage, transmission, or clandestine placement in a public file system. The watermark may be used for the subliminal marking of a source of a file, its creation, or for tagging copyrighted information.

Data processing is disclosed including acquiring a first target image to be embedded with information and to-be-embedded information, acquiring, using the first target image, a second target image corresponding to the first target image, the second target image corresponding to an image including low-luminance pixels in the first target image, the low-luminance pixels being pixels having a luminance no higher than a luminance threshold value in the first target image, selecting candidate image areas from the second target image, determining a target embedding position for the to-be-embedded information in the first target image based on the candidate image areas, and embedding the to-be-embedded information in the target embedding position in the first target image.

A method of embedding a bit or more of watermark data in a video signal to be entropy coded, wherein the video signal may be a block with levels, wherein the method may include: obtaining the watermark data; and obtaining a value of a first watermarked level on the basis of a first level of the block by processing the value of the first watermarked level. There also is a method of detecting a watermark in a video signal, the video signal having been entropy decoded and with a block with a first watermarked level, wherein the method may include: receiving the video signal; obtaining at least one bit of watermark data w.sub.i′ on the basis of the first watermarked level; and determining a tampering indicator by verifying whether the obtained watermark data w.sub.i′ corresponds with watermark data w.sub.i.

Provided are a watermark adding method and apparatus, a storage medium and a device. The method includes steps described below. To-be-added watermark information is acquired, and a time offset is determined according to the watermark information; a video frame rate is acquired, and time information of a frame image in a video is determined according to the video frame rate; and offset processing is performed on the time information according to the time offset to add the watermark information to the video.