Systems, computer program products, and methods are described herein for preserving image and acoustic sensitivity using reinforcement learning. The present invention is configured to initiate a file editing engine on the audiovisual file to separate the audiovisual file into a video component and an audio component; initiate a convolutional neural network (CNN) algorithm on the video component to identify one or more sensitive portions in the one or more image frames; initiate an audio word2vec algorithm on the audio component to identify one or more sensitive portions in the audio component; initiate a masking algorithm on the one or more image frames and the audio component; generate a masked video component and a masked audio component based on at least implementing the masking action policy; and bind, using the file editing engine, the masked video component and the masked audio component to generate a masked audiovisual file.

The present invention relates to an electronic voting system and an electronic voting method. The system for electronic voting includes an operation computer including at least one processor and a memory coupled to the processor, wherein the processor causes the system to: perform user authentication of voting participants who wish to participate in the online electronic voting; anonymize information of the voting participants whose the user authentication has been completed; give unique identification information to each of the voting participants who have completed anonymization process; and collect the voting information that the electronic voting has been conducted using the unique identification information given to the voting participants, and count the collected voting information as voting results.

An anonymization apparatus (100) includes an anonymization unit (120), a plurality of attack units (131), a degree of safety calculation unit (133), and a parameter adjustment unit (140). The anonymization unit (120) generates anonymized data. Each of the plurality of attack units (131) generates re-identification data that corresponds to the anonymized data using a re-identification attack algorithm that differs from each other. The degree of safety calculation unit (133) calculates a degree of safety of each piece of the re-identification data that each of the plurality of attack units (131) generated. The parameter adjustment unit (140) adjusts an anonymization parameter in a case where at least one of the degrees of safety does not satisfy a degree of safety standard.

A system, method, device, and platform for performing a gaming utilizing blockchain. A player profile is created in response to information received from a player. Gaming information is received from the player associated with the one or more games. Selections are assigned to the player for the one or more games utilizing player profile and the gaming information. Winners and a host with each of the one or more games of the one or more games are compensated once the one or more games are completed. The player profile, the gaming information, the selections, and the winners are documented utilizing the blockchain.

Embodiments for a system and method of selecting data protection policies for a new system, by collecting user, policy, and asset metadata for a plurality of other users storing data dictated by one or more protection policies. The collected metadata is anonymized with respect to personal identifying information, and is stored in an anonymized analytics database. The system receives specific user, policy and asset metadata for the new system from a specific user, and matches the received specific user metadata to the collected metadata to identify an optimum protection policy of the one or more protection policies based on the assets and protection requirements of the new system. The new system is then configured with the identified optimum protection policy as an initial configuration.

In some embodiments, an electronic device can guide the user in setting up the device for the first time or after a factory reset. In some embodiments, an electronic device facilitates suggesting and installing applications on the electronic device during device setup. In some embodiments, an electronic device facilitates transferring settings and information from another electronic device during device setup.

Systems, computer program products, and methods are described herein for implementing multi-dimensional data obfuscation. The present invention is configured to electronically receive, from a computing device of a user, a request to implement a multi-dimensional data obfuscation on a first database; initiate a data obfuscation engine on the first database based on at least receiving the request, wherein initiating further comprises: determining one or more data types associated with the one or more data artifacts; determining one or more exposure levels of the one or more data artifacts; retrieving, from a data obfuscation repository, one or more data obfuscation algorithms; and implementing the one or more data obfuscation algorithms on the one or more data artifacts based on at least the one or more data types; and generate an obfuscated first database based on at least initiating the data obfuscation engine on the first database.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and computing entities for predictive data protection using a data protection policy determination machine learning model. In one embodiment, a method is provided comprising: processing a historical data corpus using the data protection policy determination machine learning model to generate a dynamic data protection policy update describing inferred data protection instructions; determining an attestation subset of the inferred data protection instructions by comparing the instructions and prior data protection instructions described by an existing data protection policy; for each inferred data protection instruction in the attestation subset, determining a per-instruction attestation determination based on end-user feedback; generating an updated data protection policy by updating the existing policy in accordance with each inferred instruction in the attestation subset whose per-instruction attestation determination describes an affirmative attestation determination; and performing the predictive data protection using the updated data protection policy.

One embodiment of the invention provides a method for speaker identity and content de-identification under privacy guarantees. The method comprises receiving input indicative of privacy protection levels to enforce, extracting features from a speech recorded in a voice recording, recognizing and extracting textual content from the speech, parsing the textual content to recognize privacy-sensitive personal information about an individual, generating de-identified textual content by anonymizing the personal information to an extent that satisfies the privacy protection levels and conceals the individual's identity, and mapping the de-identified textual content to a speaker who delivered the speech. The method further comprises generating a synthetic speaker identity based on other features that are dissimilar from the features to an extent that satisfies the privacy protection levels, and synthesizing a new speech waveform based on the synthetic speaker identity to deliver the de-identified textual content. The new speech waveform conceals the speaker's identity.

Computer-implemented techniques for managing transactions of machine learning algorithm updates are described. In one embodiment, a computer-implemented is provided that comprises receiving, by a system operatively coupled to a processor, a request for an update to a machine learning model associated with a software program, wherein the request is received in accordance with a defined blockchain protocol, and wherein the request comprises model development data used in association with optimization of an instance of the machine learning model. The method further comprises, employing, by the system, a blockchain network to facilitate managing fulfillment of the request.