Abstract: A method for performing an application migration operation includes initiating the application migration operation to migrate an application from a source device to a target device, where the source device includes a source data migration agent and the target device comprises a target data migration agent. The method also includes initiating an active scan of network traffic at a transmission control protocol layer. The method further includes establishing a secure data path between the source device and the target device. In addition, the method includes beginning migration of the application from the source device to the target device using the secure data path. Moreover, the method includes making a first determination, using the active scan, that a data packet is associated with suspicious activity and rejecting the data packet based on the first determination.

Abstract: An apparatus comprises a processing device configured to receive system state information corresponding to one or more devices, to predict a usage frequency of the system state information using one or more machine learning models, and to determine, based at least in part on the usage frequency, a compression level for storage of the system state information. The compression level is applied to the system state information to generate at least one compressed file for transmission to a database.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for deep video understanding with large language models. An example embodiment operates by determining a relationship between respective first and second visual elements for each of a plurality of frames of a content item based on respective element types and respective locations for the respective first and second visual elements. For each of the plurality of frames, a respective visual prompt is generated describing the relationship between the respective first and second visual elements. Based on an audio-to-text conversion of audio content associated with the frame or classification of aural elements of the audio content, a respective audio prompt describing the audio content associated with each frame is generated.

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for personalizing a user interface (UI) of a media device and/or content presented thereby. An example embodiment operates by obtaining a first natural language user input, providing the first natural language user input to a personalization language model that is configured to interpret different natural language user inputs to respectively determine different update tasks invoked thereby, the different update tasks including a UI update task and a content update task, receiving from the model a first update task determined thereby based at least on the first natural language user input, generating one or more first application programming interface (API) calls based on the first update task, and placing the one or more first API calls to a service that implements the first update task based on the one or more first API calls.

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for personalizing a user interface (UI) of a media device and/or content presented thereby. An example embodiment operates by obtaining a first natural language user input, providing the first natural language user input to a personalization language model that is configured to interpret different natural language user inputs to respectively determine different update tasks invoked thereby, the different update tasks including a UI update task and a content update task, receiving from the model a first update task determined thereby based at least on the first natural language user input, generating one or more first application programming interface (API) calls based on the first update task, and placing the one or more first API calls to a service that implements the first update task based on the one or more first API calls.

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for personalizing a user interface (UI) of a media device and/or content presented thereby. An example embodiment operates by obtaining a first natural language user input, providing the first natural language user input to a personalization language model that is configured to interpret different natural language user inputs to respectively determine different update tasks invoked thereby, the different update tasks including a UI update task and a content update task, receiving from the model a first update task determined thereby based at least on the first natural language user input, generating one or more first application programming interface (API) calls based on the first update task, and placing the one or more first API calls to a service that implements the first update task based on the one or more first API calls.

Abstract: A method for providing ransomware training includes conducting a skill assessment for a user to determine a user performance level of the user; determining user attributes associated with the user, and user attributes include a user type, a user role, and a list of providers associated with the user; generating a training exercise including a simulated attack, and generating the simulated attack includes identifying a real-world ransomware attack, determining attack attributes of the real-world ransomware attack, and generating the simulated attack based on the attack attributes, the user attributes, and the user performance level; conducting the training exercise by sending the simulated attack to the user; receiving an attack response from the user, where the attack response includes the user's response to the simulated attack; and providing feedback to the user based on the attack response, the user attributes, and the user performance level.

Abstract: A method for enhancing data security includes receiving data. The method includes obtaining a plurality of contextual factors associated with the data. The further method includes determining an encryption level based on at least one of the contextual factors. The method further includes determining a type of encryption based on the encryption level. The method further includes encrypting the data using the type of encryption to generate encrypted data. The method further includes associating an access control level with the encrypted data to generate associated encrypted data. The method also includes determining a storage location for the associated encrypted data based on the encryption level, wherein determining the storage location is based on a data sensitivity associated with the data or a compliance rule. The method further includes sending the associated encrypted data to the storage location.

Abstract: A method for performing an application migration operation includes initiating the application migration operation to migrate an application from a source device to a target device, where the source device includes a source data migration agent and the target device comprises a target data migration agent. The method also includes initiating an active scan of network traffic at a transmission control protocol layer. The method further includes establishing a secure data path between the source device and the target device. In addition, the method includes beginning migration of the application from the source device to the target device using the secure data path. Moreover, the method includes making a first determination, using the active scan, that a data packet is associated with suspicious activity and rejecting the data packet based on the first determination.

Abstract: A method and system for secure payment transactions using direct processor communication is provided. The method includes creating a payment invoice by the merchant using a payment facilitating application provided by a payment provider. Further, the method includes sending the payment invoice to a consumer in real-time by either scanning a payment invoice code or tapping a consumer's communication device to transfer the invoice data. Further, the method includes processing payment by the consumer using a payment application or manually entering card details on the consumer's device, without transmitting secret card details to the merchant. Furthermore, the method includes updating the merchant payment invoice automatically upon completion of the payment transaction.

Abstract: Systems and methods for content customization are provided. One aspect of the systems and methods includes receiving dynamic characteristics for a plurality of users, wherein the dynamic characteristics include interactions between the plurality of users and a digital content channel; clustering the plurality of users in a plurality of segments based on the dynamic characteristics using a machine learning model; assigning a user to a segment of the plurality of segments based on static characteristics of the user; and providing customized digital content for the user based on the segment.

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations thereof, for training a conversational recommendation system. An embodiment generates a probabilistic pseudo-user neural network model based on at least one interest probability distribution corresponding to a pseudo-user profile. The embodiment trains, using the pseudo-user neural network model, the conversational recommendation system to learn a recommendation policy, where the conversational recommendation system includes an interest-exploration engine and a prompt-decision engine. The training includes performing an iterative learning process that includes selecting an interest-exploration strategy based on one or more of the following: an interest-exploration policy, an earlier pseudo-user response generated by the pseudo-user neural network model, content data, and pseudo-user interaction history.

Abstract: A method comprises receiving a data packet configured in accordance with a first network protocol version, and converting a header portion of the data packet to be configured in accordance with a second network protocol version. The converting comprises identifying a source network protocol address for a source of the data packet in the header portion in accordance with the second network protocol version, and identifying a destination network protocol address for a destination of the data packet in the header portion in accordance with the second network protocol version.

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for recommending content to a user. An embodiment identifies a first set of content items based at least on a first set of weights respectively associated with different user interests, causes the first set of content items to be presented to the user, determines a measure of user interaction with the first set of content items, provides the measure of user interaction to one of a multi-arm bandit (MAB), contextual MAB, or reinforcement learning model that selects, based at least on the state information and the measure of user interaction, a second set of weights respectively associated with the different user interests, identifies a second set of content items based at least on the second set of weights, and causes the second set of content items to be presented to the user.

Abstract: Methods, apparatus, and processor-readable storage media for automatically determining internal state information for devices using artificial intelligence techniques are provided herein. An example computer-implemented method includes identifying one or more objects in image data associated with at least one device by processing at least a portion of the image data using one or more artificial intelligence techniques; performing a comparison of at least a portion of the one or more identified objects to a predetermined set of one or more objects associated with the at least one device; determining internal state information attributed to the at least one device based at least in part on results of the comparison; and performing one or more automated actions based at least in part on the internal state information.

Abstract: A method for repairing a memory device with faulty memory cells. The method includes defining a RA environment comprising a location of each of the faulty memory cells and a plurality of SR and a plurality of SC. The method further includes repairing the faulty memory cells based on an RA training process using the defined RA environment and mapping of the location of each faulty memory cell with the plurality of SC or SR. The method further includes training, based on a determination that indicates the at least one faulty memory cell among the faulty memory cells is left unrepaired and the at least one SC or SR is remaining, a first NN to perform an action for repairing of the faulty memory cells such that a maximum number of faulty memory cells are reparable and a minimum number of SC and SR are utilized during the repairing.

Abstract: A method for managing an authentication includes establishing, by a server device, a secured network channel with a client, providing, via the secured network channel, a private key to the client, after the providing, obtaining, from the client, a request for establishing a session with the client via a second network channel, in response to the request: sending a challenge request to the client, obtaining a challenge response associated with the challenge request, wherein the challenge response specifies a first challenge answer, performing a challenge processing using a private key to generate a second challenge answer, making a determination, using the first challenge answer and the second challenge answer, that the client is authenticated, and based on the determination, initiating the session with the client.

Abstract: A method for managing data replication includes: identifying data being used by an application programming interface (API), in which the data is stored in a source device; tagging the data based on a usage level of the data by the API; obtaining a predicted probability of the usage level of the data; making a first determination that the data is tagged as important data and the predicted probability of the usage level of the data is low; and replicating, based on the first determination, the data from the source device to a target device.

Abstract: A method for managing data migration includes: receiving, by a target storage device, a migration request for migration of application data from a source storage device to the target storage device, in response to the migration request: sending a security remote security script to the source storage device, obtaining a response based on execution of the security remote security script on the source storage device, performing a security classification on the source storage device based on the response to obtain a security tag for the source storage device, determining a migration strategy for the migration of the application data from the source storage device based on the security tag, and implementing the migration strategy to migrate the application data from the source storage device to the target storage device.

Abstract: A method for managing restoration includes receiving, by a restoration orchestrator, a restoration request for the restoration by a restoring device, in response to the restoration request: identifying a downtime preparation time for the restoration, collecting, during the downtime preparation time, service requests from the restoring device, forwarding the service requests to a digital twin device, after the forwarding, making a determination that the downtime preparation time is complete, and based on the determination, initiating a re-servicing of the restoring device, wherein the restoration is complete after the determination.