Abstract: A transportation data aggregator platform (“TDAP”) receives, from a carrier computing device, a selection of one or more electronic logging device (“ELD”) provider systems associated with ELDs of vehicles of a carrier. The TDAP, for each of the one or more selected ELD provider systems, (1) displays, on the computing device of the carrier computing device, a request for credentials associated with the selected ELD provider system, (2) receives, via the carrier computing device, an input comprising the credentials, (3) communicates, to the ELD provider system, the credentials, and (4) receives, from the ELD provider system, a response confirming a validity of the communicated credentials. The TDAP, in response to receiving the response for each of the one or more selected ELD provider systems, generates a letter of authorization (“LOA”) and accesses ELD data logged by ELDs of the carrier from the one or more selected ELD provider systems.

Abstract: Methods, systems, and media for providing personalized notifications to video viewers are provided. In some embodiments, the method comprises: receiving, using a hardware processor, one or more prompts to be presented in association with a video from a user account associated with the video; receiving, from the user account associated with the video, one or more notifications, wherein each of the one or more prompts is associated with one of the one or more notifications; causing the one or more prompts to be presented in association with presentation of the video to a user; receiving an indication that a first prompt of the one or more of the prompts was selected by the user; causing a notification associated with the first prompt to be presented to the user in response to receiving the indication.

Abstract: Provided is a data intermediary system, comprising a processor and a storage unit. The storage unit stores therein usage information indicating usage of services. The processor acquires information indicating a data item that needs to be provided by a user as required by a provider of a first service that the user wishes to use, based on terms of use of the first service, selects a second service from services that the user has used in the past, based on the usage information, extracts a difference between the required data items and data items provided based on terms of use of the second service, outputs information indicating the extracted difference, and controls, when the user has accepted the terms of use of the first service, a flow of data from a provider holding the required data to the provider that provides the first service.

Abstract: A method may include receiving, by a computing system and from a first device, first data. The first data may be based at least in part on a first output from a first instance of a model processed by the first device. The method may further include receiving, by the computing system and from the first device, second data that was processed by the first instance of the model to produce the first output. The method may also include processing, by the computing system, the second data with at least a portion of a second instance of the model to produce a second output. The method may additionally include determining, by the computing system, third data based at least in part on the second output. Further, the method may include determining, by the computing system, that the third data is consistent with the first data.

Abstract: The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes sending a block command for an object to each application in a multiple-application landscape that includes a master data distribution application. A blocking status is received from each application that indicates whether the application successfully blocked the object in response to the block command. An overall blocking status is determined based on the received blocking statuses. In response to determining that at least one application failed to block the object, an unblock command is sent to each application. An unblocking status is received from each application and an overall unblocking status is determined. In response to determining that at least one application failed to unblock the object, a redistribution request is sent to the master data distribution application to redistribute the object to applications that failed to unblock the object.

Abstract: A policy evaluation apparatus (2000) acquires, with respect to each of a plurality of control groups (10) including an evaluation target group, control policies (20). Each of the control policy (20) indicates execution permission/non-permission of an application. Further, the policy evaluation apparatus (2000) compares an evaluation target policy being the control policy (20) of the evaluation target group with other plurality of control policies (20), and generates evaluation information (30) based on the comparison result.

Abstract: A privacy system includes a computing device configured to obtain user transactional data characterizing at least one transaction of a user on an ecommerce marketplace and to determine a privacy vulnerability score of the user by comparing the transactional data to a user vulnerability distribution. The computing device is also configured to send the privacy vulnerability score to a personalization engine.

Abstract: Systems, methods, and apparatus are provided for intelligent cybersecurity processing of a product update. A fetcher application may access an updated version of a software product, a prior version of the product, and a version control system for the product. A malicious software identification engine may process the data using batch or stream processing to identify suspect code and metadata anomalies in the updated version. The engine may decompile executable binary code to obtain source code for the updated version and the prior version. A machine learning engine may receive input from the malicious software identification engine and classify the input using an NER-based machine learning model. Based on output from the machine learning engine, a control dashboard may block installation of a malicious product update.

Abstract: Aspects of the disclosure relate to voice biometric authentication in a virtual assistant. In some embodiments, a computing platform may receive, from a user device, an audio file comprising a voice command to access information related to a user account. The computing platform may retrieve one or more voice biometric signatures from a voice biometric database associated with the user account, and apply a voice biometric matching algorithm to compare the voice command of the audio file to the one or more voice biometric signatures to determine if a match exists between the voice command and one of the one or more voice biometric signatures. In response to determining that a match exists, the computing platform may retrieve information associated with the user account, and then send, via the communication interface, the information associated with the user account to the user device.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: A Proof of View verification system is disclosed. The Proof of View verification system has a Non-Fungible Token smart contract module, comprising computer-executable code stored in non-volatile memory, a Proof of View smart contract module, comprising computer-executable code stored in non-volatile memory, a processor, and a verifier network. The Non-Fungible Token smart contract module, the Proof of View smart contract module, the processor, and the verifier network are configured to transfer a data of a non-fungible token to the Non-Fungible Token smart contract module and generate an event metadata based on the data of the non-fungible token, transfer the event metadata to the Proof of View smart contract module, and generate an event hash using the verifier network and transferring the event hash from the verifier network to the Proof of View smart contract module.

Abstract: A security platform architecture is described herein. The security platform architecture includes multiple layers and utilizes a combination of encryption and other security features to generate a secure environment.

Abstract: An example method includes initializing a configuration file for a machine learning model, wherein the initializing is performed in response to receiving a request from a user, and wherein the configuration file comprises a plurality of sections that is configurable by the user, configuring at least one parameter of a feature engineering rules section of the configuration file, wherein the configuring the at least one parameter of the feature engineering rules section is based on a first value provided by the user, configuring at least one parameter of an algorithm definitions section of the configuration file, wherein the configuring the at least one parameter of the algorithm definitions section is based on a second value provided by the user, and populating the configuration file using the feature engineering rules section as configured and the algorithm definitions section as configured, to generate the machine learning model.

Abstract: The present disclosure relates to processing operations that execute image classification training for domain-specific traffic, where training operations are entirely compliant with data privacy regulations and policies. Image classification model training, as described herein, is configured to classify meaningful image categories in domain-specific scenarios where there is unknown data traffic and strict data compliance requirements that result in privacy-limited image data sets. Iterative image classification training satisfies data compliance requirements through a combination of online image classification training and offline image classification training. This results in tuned image recognition classifiers that have improved accuracy and efficiency over general image recognition classifiers when working with domain-specific data traffic. One or more image recognition classifiers are independently trained and tuned to detect an image class for image classification.

Abstract: Data is received that specifies a bound for an adversarial posterior belief ?c that corresponds to a likelihood to re-identify data points from the dataset based on a differentially private function output. Privacy parameters ?, ? are then calculated based on the received data that govern a differential privacy (DP) algorithm to be applied to a function to be evaluated over a dataset. The calculating is based on a ratio of probabilities distributions of different observations, which are bound by the posterior belief ?c as applied to a dataset. The calculated privacy parameters are then used to apply the DP algorithm to the function over the dataset. Related apparatus, systems, techniques and articles are also described.

Abstract: Methods, computer-readable media, and processing systems are disclosed for establishing a data sharing community for an event of an event type. For example, a processing system including at least one processor may detect, via at least one data source device, a trigger condition for an event of an event type, and establish a data sharing community for the event, the data sharing community including a plurality of data sources, the plurality of data sources including the at least one data source device, and a plurality of data consumers, where the establishing includes setting respective permission levels for the data consumers. The processing system may further collect data from the plurality of data sources in accordance with the event type, and provide at least a first portion of the data to at least a first data consumer in accordance with a respective permission level of at least the first data consumer.

Abstract: In one approach, a method includes: receiving a reference login event input from a user, the reference login event input being associated with a first session of the user logging into an account; receiving a new login event input from the user, the new login event input being associated with a second session of the user logging into the account; accessing a machine learning model, wherein the machine learning model is trained using data selected based on a similarity of behavior between different users; and authenticating, with the machine learning model, the user for the account, based at least in part on the reference login event input and the new login event input. In examples, the reference and new login event inputs comprise one or more items of biometric data generated by interaction of the user in a web environment and/or a mobile environment for logging into the account.

Abstract: Disclosed is a communication method for a device, a first cloud platform and a second cloud platform. The communication method includes obtaining, by the first cloud platform, a first access token from the second cloud platform. The first access token is configured for the first cloud platform to access a second resource link of a second device on the second cloud platform, and the second device is connected to the second cloud platform. The method also includes obtaining, by the first cloud platform, the second resource link based on the first access token. The method further includes determining, by the first cloud platform, a first resource link of the second device on the first cloud platform based on the second resource link. The first resource link is configured for a first device connected to the first cloud platform to communicate with the second device.

Abstract: Provided is a data protection method which includes: receiving transaction data which includes a first hash value obtained from history information of a home; obtaining, from a data server, a second hash value computed by the data server performing computation processing on encrypted history information without decrypting the encrypted history information, the encrypted history information being history information of the home encrypted using a secure computation method which enables computation without decrypting the encrypted history information, the encrypted history information being obtained from the home; verifying the transaction data, and determining whether the first hash value and the second hash value match; and when a validity of the transaction data is verified and the first hash value and the second hash value match, recording the transaction data in a distributed ledger.

Abstract: Systems, computer program products, and methods are described herein for secure access control using dynamic resource replication. The present invention is configured to electronically receive, from a computing device of a user, a request to generate a resource access path to access a resource; determine one or more resource requirements associated with the resource; determine an authentication level associated with the user; initiate a resource replication engine on the one or more resource requirements and the authentication level associated with the user; determine, using the resource replication engine, that the one or more requirements and the authentication level associated with the user meets one or more conditions for a replication process; and generate, using the resource replication engine, the resource access path and a plurality of replicate resource access paths.