Abstract: Identification of an electronic communication containing specific information is provided. Content of the electronic communication may be evaluated by a machine-learning model, and based on an evaluation of the content, it may be determined that the electronic communication contains the specific information. The electronic communication may be tagged with tag information indicating that the electronic communication contains the specific information, and transmission of the electronic communication may be blocked based on the tag information.

Abstract: A method can include intercepting, by an interceptor positioned between a transfer system and a transfer settlement system, a transaction prior to the transaction being provided to the transfer settlement system. The method can include confirming that data from the transaction matches information in an immutable ledger to which parameters of the transaction have been provided by a notary system that confirms the parameters of the transaction and applies a signature using a private key to the transaction in response to confirming the parameters. The method can include, in response to confirming that the data matches the information, providing the transaction for settlement by the transfer settlement system.

Abstract: Identification of an electronic communication containing specific information is provided. Content of the electronic communication may be evaluated by a machine-learning model, and based on an evaluation of the content, it may be determined that the electronic communication contains the specific information. The electronic communication may be tagged with tag information indicating that the electronic communication contains the specific information, and transmission of the electronic communication may be blocked based on the tag information.

Abstract: Targeted lockdown of a computer system for an identified vulnerability is provided. The targeted lockdown includes configuring a vulnerability lockdown module implemented on a computer system to perform targeted actions to change a configuration of the computer system. The targeted actions may be configured based at least in part on a type of data stored on the computer system and a potential severity of an impact on the computer system if the vulnerability is exploited. The vulnerability lockdown module may implement a vulnerability lockdown mode by causing the computer system to perform the targeted actions to change the configuration of the computer system by restricting functionality of portions of the computer system affected by the identified vulnerability. The targeted actions performed by the computer system may include altering a way in which a user interacts with the computer system.

Abstract: A transaction system can include a computing device with a communication port, a processor device, and a non-transitory computer-readable storage memory. The communication port can communicate data with other computing devices. The non-transitory computer-readable storage memory includes code that is executable by the processor device to perform operations. The operations include receiving parameters of a transfer, verifying the transfer using a multi-factor authentication process, in response to verifying the transfer, using a private key to countersign the transfer and return, via the communications port, a signed transfer package for execution of the transfer, and providing, via the communications port, the parameters of the transfer and countersign data to an immutable ledger.

Abstract: In various examples, as a user is speaking or presenting content during an online video conference, the data stream may be processed to generate a textual representation (e.g., transcript) of the audio and/or information relating to the video. The textual representation and/or video related information may then be processed to determine a context or one or more topic(s) of discussion. Based on the determined context/topic(s), a corresponding neural network(s) may be selected. Once a neural network has been selected, comments may be retrieved from a chat feature of the application and applied to the neural network. The neural network may then output data to indicate the relevance of the comments to the determined discussion topic. Based on the relevance of the comment, the comment may be allowed, prioritized, deleted, de-emphasized, or otherwise filtered in the chat feature.

Abstract: Account permissions and data accessibility can be modified based on level of confidence for a login attempt to the account. User activity observations corresponding to one or more login attempts to access a user account can be stored. A confidence score associated with a successful login attempt of the user account can be determined. The confidence score is based on the user activity observations. A level of access to an application with functions and data for the user account can be determined. The level of access is based on the confidence score. The level of access is associated with the functions and the data that are executable and accessible subsequent to the successful login attempt.

Abstract: In various examples, as a user is speaking or presenting content during an online video conference, the data stream may be processed to generate a textual representation (e.g., transcript) of the audio and/or information relating to the video. The textual representation and/or video related information may then be processed to determine a context or one or more topic(s) of discussion. Based on the determined context/topic(s), a corresponding neural network(s) may be selected. Once a neural network has been selected, comments may be retrieved from a chat feature of the application and applied to the neural network. The neural network may then output data to indicate the relevance of the comments to the determined discussion topic. Based on the relevance of the comment, the comment may be allowed, prioritized, deleted, de-emphasized, or otherwise filtered in the chat feature.

Abstract: Account permissions and data accessibility can be modified based on level of confidence for a login attempt to the account. User activity observations corresponding to one or more login attempts to access a user account can be stored. A confidence score associated with a successful login attempt of the user account can be determined. The confidence score is based on the user activity observations. A level of access to an application with functions and data for the user account can be determined. The level of access is based on the confidence score. The level of access is associated with the functions and the data that are executable and accessible subsequent to the successful login attempt.

Abstract: Systems and methods for generating real-time synthetic crowd responses for events, to augment the experience of event participants, remote viewers, and the like. Various sensors monitor the event in question, and various event properties are derived from their output using an event state model. These event properties, along with various event parameters such as score, time remaining, etc., are then input to a machine learning model that determines a real-time synthetic audience reaction tailored to the immediate state of the event. Reaction parameters are used to generate a corresponding crowd or audience audio signal, which may be broadcast to event participants, viewers, spectators, or anyone who may be interested. This instantaneous, realistic crowd reaction more closely simulates the experience of events with full on-site audiences, enhancing the viewing experience of both event participants and those watching.

Abstract: Verified deliveries are commonplace for various exchanges of goods, packages, and/or other items, but often require close proximity or contact between the exchanging parties or devices associated therewith—e.g., for digital or physical signature. To remedy this, system and methods described herein may leverage an ad hoc network established between a device of a provider and a device of a consumer for exchanging codes or tokens—that may be validated by an authentication service—to provide a verification process during an exchange between the parties. As a result, a safe distance may be maintained between the parties throughout the transaction—thereby avoiding exchange of germs while also increasing safety and security of both parties—and the verification process may be more reliable and secure.

Abstract: Account permissions and data accessibility can be modified based on level of confidence for a login attempt to the account. User activity observations corresponding to one or more login attempts to access a user account can be stored. A confidence score associated with a successful login attempt of the user account can be determined. The confidence score is based on the user activity observations. A level of access to an application with functions and data for the user account can be determined. The level of access is based on the confidence score. The level of access is associated with the functions and the data that are executable and accessible subsequent to the successful login attempt.

Abstract: Targeted lockdown of a computer system for an identified vulnerability is provided. The targeted lockdown includes configuring a vulnerability lockdown module implemented on a computer system to perform targeted actions to change a configuration of the computer system. The computer system may be scanned by a vulnerability scanner configured to identify vulnerabilities. In response to identifying a vulnerability, the vulnerability may be communicated to the vulnerability lockdown module and the vulnerability lockdown module may implement a vulnerability lockdown mode by causing the computer system to perform the targeted actions to change the configuration of the computer system by restricting functionality of portions of the computer system affected by the identified vulnerability.

Abstract: Systems and methods are presented for reliable transmission of time-sensitive data. In particular, various embodiments provide for the generation of compressed sequential data, where individual instances of a sequence represent differentials from prior instances in that sequence. In order to reduce an amount of data that needs to be transmitted, instances of data (such as individual video frames) can be provided using a prior video frame as a reference, sending only data for those pixel locations where the pixel value differs from the reference frame. A reference frame can include a previously-received and successfully-decoded frame, in order to minimize the impact of dropped, incomplete, or corrupted frames. In order to further reduce data transmission requirements, a reference frame can be selected which is determined to be optimal for the current frame, such as may represent a least amount of data to be transmitted for a given frame.

Abstract: A transaction system can include a computing device with a communication port, a processor device, and a non-transitory computer-readable storage memory. The communication port can communicate data with other computing devices. The non-transitory computer-readable storage memory includes code that is executable by the processor device to perform operations. The operations include receiving parameters of a transfer, verifying the transfer using a multi-factor authentication process, in response to verifying the transfer, using a private key to countersign the transfer and return, via the communications port, a signed transfer package for execution of the transfer, and providing, via the communications port, the parameters of the transfer and countersign data to an immutable ledger.

Abstract: Account permissions and data accessibility can be modified based on level of confidence for a login attempt to the account. User activity observations corresponding to one or more login attempts to access a user account can be stored. A confidence score associated with a successful login attempt of the user account can be determined. The confidence score is based on the user activity observations. A level of access to an application with functions and data for the user account can be determined. The level of access is based on the confidence score. The level of access is associated with the functions and the data that are executable and accessible subsequent to the successful login attempt.

Abstract: Account permissions and data accessibility can be modified based on level of confidence for a login attempt to the account. User activity observations corresponding to one or more login attempts to access a user account can be stored. A confidence score associated with a successful login attempt of the user account can be determined. The confidence score is based on the user activity observations. A level of access to an application with functions and data for the user account can be determined. The level of access is based on the confidence score. The level of access is associated with the functions and the data that are executable and accessible subsequent to the successful login attempt.

Abstract: A transaction system can include a computing device with a communication port, a processor device, and a non-transitory computer-readable storage memory. The communication port can communicate data with other computing devices. The non-transitory computer-readable storage memory includes code that is executable by the processor device to perform operations. The operations include receiving parameters of a transfer, verifying the transfer using a multi-factor authentication process, in response to verifying the transfer, using a private key to countersign the transfer and return, via the communications port, a signed transfer package for execution of the transfer, and providing, via the communications port, the parameters of the transfer and countersign data to an immutable ledger.

Abstract: Systems and methods for generating real-time synthetic crowd responses for events, to augment the experience of event participants, remote viewers, and the like. Various sensors monitor the event in question, and various event properties are derived from their output using an event state model. These event properties, along with various event parameters such as score, time remaining, etc., are then input to a machine learning model that determines a real-time synthetic audience reaction tailored to the immediate state of the event. Reaction parameters are used to generate a corresponding crowd or audience audio signal, which may be broadcast to event participants, viewers, spectators, or anyone who may be interested. This instantaneous, realistic crowd reaction more closely simulates the experience of events with full on-site audiences, enhancing the viewing experience of both event participants and those watching.