An image processing system includes circuitry. The circuitry accepts, from a user, an input of information to be registered. The circuitry registers the inputted information as registered information. The circuitry generates tracing data to be used for tracing the registered information. The circuitry outputs the tracing data. The circuitry associates access authorization to an access log for the registered information with the tracing data. The circuitry accepts an input of the tracing data. The circuitry acquires the access log that is associated with the inputted tracing data, and displays the acquired access log.

An image processing system includes circuitry. The circuitry accepts, from a user, an input of information to be registered. The circuitry registers the inputted information as registered information. The circuitry generates tracing data to be used for tracing the registered information. The circuitry outputs the tracing data. The circuitry associates access authorization to an access log for the registered information with the tracing data. The circuitry accepts an input of the tracing data. The circuitry acquires the access log that is associated with the inputted tracing data, and displays the acquired access log.

In one embodiment, a computer-implemented method performed by a data processing (DP) accelerator, includes receiving, at the DP accelerator, first data representing a set of training data from a host processor; receiving, at the DP accelerator, a watermark kernel from the host processor; and executing the watermark kernel within the DP accelerator on an artificial intelligence (AI) model. The watermark kernel, when executed, is configured to: generate a new watermark by inheriting an existing watermark from a data object of the set of training data, train the AI model using the set of training data, and implant the new watermark within the AI model during training of the AI model. The DP accelerator then transmits second data representing the trained AI model having the new watermark implanted therein to the host processor.

In one embodiment, a computer-implemented method performed by a data processing (DP) accelerator, includes receiving, at the DP accelerator, first data representing a set of training data from a host processor; receiving, at the DP accelerator, a watermark kernel from the host processor; and executing the watermark kernel within the DP accelerator on an artificial intelligence (AI) model. The watermark kernel, when executed, is configured to: generate a new watermark by inheriting an existing watermark from a data object of the set of training data, train the AI model using the set of training data, and implant the new watermark within the AI model during training of the AI model. The DP accelerator then transmits second data representing the trained AI model having the new watermark implanted therein to the host processor.

An audio watermark addition method is provided, and includes: A playback terminal obtains first audio in real time, embeds an audio watermark into the first audio, where the audio watermark is associated with the playback terminal; and plays the first audio embedded with the audio watermark.

A method for generating an electronic signature for an electronic document is implemented by an electronic device that is in communication with a stylus pen and a handwriting input device that includes a writing area. The method includes: initiating a signature input procedure associated with the electronic document; obtaining a signature pattern and an experienced pressure dataset recorded by the handwriting input device during the signature input procedure, and obtaining a fingerprint dataset and an applied pressure dataset recorded by the stylus pen during the signature input procedure; determining whether the experienced pressure dataset corresponds with the applied pressure dataset; and in the case where the experienced pressure dataset corresponds with the applied pressure dataset, generating a signed electronic document by presenting the signature pattern on a part of the electronic document and embedding the fingerprint dataset in the signature pattern.

The invention resides in a method of placing a code, having a plurality of digits, in original data having media data including audio data, such as a music video, piece of music or music track, to produce coded data. The method determining an area of original data where a digit of the code can be placed to inhibit detection using a placement criteria. A coding strategy determines at least one of the format or location of a digit of the code in coded data. The or each digit of the code has a melodic or sympathetic relationship with a characteristic, such as an audio characteristic, of the corresponding original data in the at the location in which it is placed. Digits are added to the original data and outputting coded data. Similarly, the invention resides in a method for decoding and devices and systems for implementing said methods.

The invention resides in a method of placing a code, having a plurality of digits, in original data having media data including audio data, such as a music video, piece of music or music track, to produce coded data. The method determining an area of original data where a digit of the code can be placed to inhibit detection using a placement criteria. A coding strategy determines at least one of the format or location of a digit of the code in coded data. The or each digit of the code has a melodic or sympathetic relationship with a characteristic, such as an audio characteristic, of the corresponding original data in the at the location in which it is placed. Digits are added to the original data and outputting coded data. Similarly, the invention resides in a method for decoding and devices and systems for implementing said methods.

Digital Witness is a solution based on advanced cryptographic techniques to ensure data integrity, authenticity, irrefutability and confidentiality at the point of data creation. The DigiWit process guarantee is based on using strong cryptographic techniques in conjunction with PKI and public/private block-chains. DigiWit process establishes a ‘root of trust’ for a digital artifact in conjunction with notarization provided by a trusted third-party. The result is a mathematical non-repudiable guarantee that the file under audit is exactly as recorded by the author. The authenticity of the author and the root of trust are provided by the notarizing trusted third-party. Integrity of the captured data is based on the time to insert its unique signature to the block-chain public ledger. This root of trust is intended to be permissible to prove authenticity of evidence in the legal arena (e.g., images of crime scenes, contracts, etc.) based on mathematical veracity.

Digital Witness is a solution based on advanced cryptographic techniques to ensure data integrity, authenticity, irrefutability and confidentiality at the point of data creation. The DigiWit process guarantee is based on using strong cryptographic techniques in conjunction with PKI and public/private block-chains. DigiWit process establishes a ‘root of trust’ for a digital artifact in conjunction with notarization provided by a trusted third-party. The result is a mathematical non-repudiable guarantee that the file under audit is exactly as recorded by the author. The authenticity of the author and the root of trust are provided by the notarizing trusted third-party. Integrity of the captured data is based on the time to insert its unique signature to the block-chain public ledger. This root of trust is intended to be permissible to prove authenticity of evidence in the legal arena (e.g., images of crime scenes, contracts, etc.) based on mathematical veracity.