Abstract: One example method includes identifying dissimilar items in a data set. A data set may be walked one or more times and the nodes or vertices of the data set may be scored based on the number of times the nodes are touched during the walks. Scores below a threshold score are determined to be dissimilar nodes in the data set. This allows a diverse set of nodes to be identified. A dissimilar data set may be used to prevent unintentional bias in algorithmic training.

Abstract: Techniques for function execution environment selection for a decomposed application are provided. In one example, an apparatus comprises at least one processing platform configured to execute a portion of an application program in a first virtual computing element, wherein the application program comprises one or more portions of marked code, receive a request for execution of one of the one or more portions of marked code, decide whether to execute the portion of marked code identified in the request in the first virtual computing element or in a second virtual computing element, determine an execution environment from one or more execution environments specified in the marked code for the second virtual computing element to execute the marked code, when it is decided to execute the portion of the marked code in the second virtual computing element, and cause the portion of marked code identified in the request to be executed.

Abstract: A method for securing a secret of a client using an escrow agent operatively connected to the client includes initiating enrollment of the client with the escrow agent, wherein the enrollment results the escrow agent generating a key pair comprising a public key and a private key, obtaining the public key from the escrow agent, wherein the private key is not shared with the client, encrypting the secret with the public key to obtain an encrypted secret, and storing the encrypted secret on the client.

Abstract: One example method includes collecting an audio segment that includes audio data generated by a user, analyzing the audio data to identify an emotion expressed by the user, computing start and end indices of a video segment, selecting video data that shows the emotion expressed by the user, using the video data and the start and end indices of the video segment to modify a face of the user as the face appears in the video segment so as to generate modified face frames, and stitching the modified face frames into the video segment to create a modified video segment with the emotion expressed by the user, and the modified video segment includes the audio data generated by the user.

Abstract: One example method includes capturing audio data at a client engine while outputting an output video, the output video being based upon an original video stored at the client engine, delivering the captured audio data to a prediction engine upon the captured audio data being captured for a pre-determined time, receiving from the prediction engine substitute frame data used by the client engine to stitch one or more frames into the original video stored at the client engine, and following stitching the one or more frames into the output video to generate an altered output video, outputting the captured audio data and the altered video from the client engine.

Abstract: One example method includes capturing audio data at a client engine while outputting an output video, the output video being based upon an original video stored at the client engine, delivering the captured audio data to a prediction engine upon the captured audio data being captured for a pre-determined time, receiving from the prediction engine substitute frame data used by the client engine to stitch one or more frames into the original video stored at the client engine, and following stitching the one or more frames into the output video to generate an altered output video, outputting the captured audio data and the altered video from the client engine.

Abstract: One example method includes crawling data included in a dataset, based on the crawling of the data, creating and/or obtaining metadata concerning the data, crawling the metadata and obtaining information about a data change event involving the data, based on the crawling of the metadata, creating a meta label that documents occurrence of the data change event, and associating the meta label with the metadata. An analysis of the data, metadata, and meta label, may be performed and a trigger generated based on the analysis.

Abstract: A method for verifying a secret decryption of an escrow agent by a client operatively connected to the escrow agent includes initiating enrollment of the client with the escrow agent, wherein the enrollment results the escrow agent generating a key pair comprising a public key and a private key, obtaining the public key from the escrow agent, wherein the private key is not shared with the client, encrypting the secret with the public key to obtain an encrypted secret, after encrypting the secret, encrypting, based on a verification trigger, a verification value using the public key to obtain an encrypted verification value, sending the encrypted verification value to the escrow agent, obtaining a secret decryption response from the escrow agent, making a determination, based on the secret decryption response, that the escrow agent is not capable of decrypting the secret, and based on the determination, performing a remediation action.

Abstract: One example method includes identifying dissimilar items in a data set. A data set may be walked one or more times and the nodes or vertices of the data set may be scored based on the number of times the nodes are touched during the walks. Scores below a threshold score are determined to be dissimilar nodes in the data set. This allows a diverse set of nodes to be identified. A dissimilar data set may be used to prevent unintentional bias in algorithmic training.

Abstract: A method for verifying a secret decryption of an escrow agent by a client operatively connected to the escrow agent includes initiating enrollment of the client with the escrow agent, wherein the enrollment results the escrow agent generating a key pair comprising a public key and a private key, obtaining the public key from the escrow agent, wherein the private key is not shared with the client, encrypting the secret with the public key to obtain an encrypted secret, after encrypting the secret, encrypting, based on a verification trigger, a verification value using the public key to obtain an encrypted verification value, sending the encrypted verification value to the escrow agent, obtaining a secret decryption response from the escrow agent, making a determination, based on the secret decryption response, that the escrow agent is not capable of decrypting the secret, and based on the determination, performing a remediation action.

Abstract: A method for securing a secret of a client using an escrow agent operatively connected to the client includes initiating enrollment of the client with the escrow agent, wherein the enrollment results the escrow agent generating a key pair comprising a public key and a private key, obtaining the public key from the escrow agent, wherein the private key is not shared with the client, encrypting the secret with the public key to obtain an encrypted secret, and storing the encrypted secret on the client.

Abstract: A system in one embodiment comprises a first endpoint device that is configured to communicate with a second endpoint device using a given communication protocol. The first endpoint device is configured to monitor a communication session under the given communication protocol and to generate monitoring data associated with the communication session. The first endpoint device is configured to determine that a designated network condition has occurred based at least in part on the monitoring data. The first endpoint device is configured to activate a performance monitoring component based at least in part on the determination that the designated network condition has occurred and to generate performance data utilizing the activated performance monitoring component. The first endpoint device is configured to anonymize and store the performance data.

Abstract: A system in one embodiment comprises a first endpoint device that is configured to communicate with a second endpoint device using a given communication protocol. The first endpoint device is configured to monitor a communication session under the given communication protocol and to generate monitoring data associated with the communication session. The first endpoint device is configured to determine that a designated network condition has occurred based at least in part on the monitoring data. The first endpoint device is configured to activate a performance monitoring component based at least in part on the determination that the designated network condition has occurred and to generate performance data utilizing the activated performance monitoring component. The first endpoint device is configured to anonymize and store the performance data.

Abstract: A system in one embodiment comprises a first endpoint device that is configured to communicate with a second endpoint device using a given communication protocol. The first endpoint device is configured to monitor a communication session under the given communication protocol and to generate monitoring data associated with the communication session. The first endpoint device is configured to determine that a designated network condition has occurred based at least in part on the monitoring data. The first endpoint device is configured to activate a performance monitoring component based at least in part on the determination that the designated network condition has occurred and to generate performance data utilizing the activated performance monitoring component. The first endpoint device is configured to anonymize and store the performance data.

Abstract: Techniques for function execution environment selection for a decomposed application are provided. In one example, an apparatus comprises at least one processing platform configured to execute a portion of an application program in a first virtual computing element, wherein the application program comprises one or more portions of marked code, receive a request for execution of one of the one or more portions of marked code, decide whether to execute the portion of marked code identified in the request in the first virtual computing element or in a second virtual computing element, determine an execution environment from one or more execution environments specified in the marked code for the second virtual computing element to execute the marked code, when it is decided to execute the portion of the marked code in the second virtual computing element, and cause the portion of marked code identified in the request to be executed.

Abstract: Techniques for dynamic decomposition of an application executing in a computing environment are provided. For example, an apparatus comprises at least one processing platform comprising one or more processing devices. The at least one processing platform is configured to execute a portion of an application program in a first virtual computing element, wherein the application program comprises one or more portions of marked code, receive a request for execution of one of the one or more portions of marked code, decide whether to execute the portion of marked code identified in the request in the first virtual computing element or in a second virtual computing element, and cause the portion of marked code identified in the request to be executed in the second virtual computing element, when it is decided to execute the portion of the marked code in the second virtual computing element.

Abstract: Techniques for dynamic decomposition of an application executing in a computing environment are provided. For example, an apparatus comprises at least one processing platform comprising one or more processing devices. The at least one processing platform is configured to execute a portion of an application program in a first virtual computing element, wherein the application program comprises one or more portions of marked code, receive a request for execution of one of the one or more portions of marked code, decide whether to execute the portion of marked code identified in the request in the first virtual computing element or in a second virtual computing element, and cause the portion of marked code identified in the request to be executed in the second virtual computing element, when it is decided to execute the portion of the marked code in the second virtual computing element.