Abstract: The present invention discloses an unmanned aerial vehicle and a method for controlling a gimbal thereof. The method for controlling a gimbal includes: generating, by a flight control system, a yaw angular speed instruction of the unmanned aerial vehicle; and controlling, by a gimbal control system, a yaw axis motor of the gimbal according to the yaw angular speed instruction of the unmanned aerial vehicle. In the present invention, the yaw axis motor of the gimbal is jointly controlled by the flight control system and the gimbal control system, so that advantages of high-precision control and quick response of the gimbal control system are maximized. The advantages are used for compensating for deficiencies of the flight control system in yaw control, thereby improving the stability of a yaw channel of the gimbal, and completely resolving frame freezing of an aerial video when the unmanned aerial vehicle yaws at a low speed.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems based on machine-learned user behavior profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account. The computing platform may capture behavioral parameters associated with the client computing device and may evaluate the behavioral parameters using a behavioral profile associated with the user account to determine a behavioral deviation score. Based on the behavioral deviation score, the computing platform may select an authentication action from a plurality of pre-defined authentication actions. Subsequently, the computing platform may generate commands directing an account portal computing platform to allow access, conditionally allow access, or prevent access based on the selected authentication action.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems using machine-learned user-account behavior profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account. The computing platform may capture one or more behavioral parameters and activity data associated with one or more interactions with one or more non-authenticated pages. Then, the computing platform may evaluate the one or more behavioral parameters and the activity data using a behavioral profile associated with the user account. Based on this evaluation, the computing platform may identify the authentication request as malicious and may generate and send one or more denial-of-access commands to prevent the client computing device from accessing the one or more secured information resources associated with the user account.

Abstract: Aspects of the disclosure relate to preventing unauthorized access to secured information systems. A computing platform may receive, from an end user desktop computing device, a request to login to a user account associated with a user account portal. In response to receiving the request, the computing platform may generate an authentication token in an authentication database and may send a notification to at least one registered device linked to the user account. After sending the notification, the computing platform may receive, from the at least one registered device, an authentication response message. If the authentication response message indicates that valid authentication input was received, the computing platform may update the authentication token to indicate that the request to login to the user account has been approved. After updating the authentication token, the computing platform may provide, to the end user desktop computing device, access to a portal interface.

Abstract: Aspects of the disclosure relate to determining optimal machine learning models. A computing platform may collect, via a network, data indicative of login activity to an enterprise resource. One or more initial features indicative of the login activity may be identified. Based on the one or more initial features, an initial test dataset and a test model may be generated. Then, the test model may be deployed in a production environment. Subsequently, the computing platform may identify one or more production feature vectors. Then, the computing platform may generate, based on the one or more production feature vectors, a training dataset. Subsequently, the computing platform may perform, for the training dataset, a data quality check. Then, the computing platform may predict, by applying Bayesian optimization to the training dataset, an optimal machine learning model. Subsequently, the computing platform may apply the optimal machine learning model to detect unauthorized activity.

Abstract: Aspects of the disclosure relate to linking channel-specific systems with a user authentication hub. In some embodiments, a computing platform may receive, from a telephone agent support computer system associated with a telephone agent channel, an authentication request for a user account. The computing platform may generate a set of one or more authentication prompts based on a set of authentication rules defined for the telephone agent channel and may provide the set of one or more authentication prompts generated based on the set of authentication rules defined for the telephone agent channel. Subsequently, the computing platform may validate one or more responses to the set of one or more authentication prompts. Based on validating the one or more responses, the computing platform may provide user account information associated with the user account to the telephone agent support computer system associated with the telephone agent channel.

Abstract: Contactless dispensing of objects from object-dispensing machines. A digital token is wirelessly communicated to the machine via short-range wireless communication, such as Near Field Communication (NFC) or the like. In response, a push notification is communicated to the user's wireless device, which includes an activatable link for launching a mobile application. In response to launching the mobile application and authenticating the user, the mobile application provides object-dispensing machine-like user interfaces that are configured to allow the user to input object requesting parameters and submit a request for objects to be dispensed from the object-dispensing machine. The request is communicated to the object-dispensing machines (or corresponding backend processing systems) and, once the request is verified, the object-dispensing machine dispenses the requested objects.

Abstract: Aspects of the disclosure relate to linking channel-specific systems with a user authentication hub. In some embodiments, a computing platform may receive, from a mobile device, an authentication request for a user account and may generate one or more authentication prompts. Subsequently, the computing platform may provide the one or more authentication prompts and may validate responses to the authentication prompts. Based on validating the responses to the authentication prompts, the computing platform may generate one or more security questions based on historical information associated with the user account. Subsequently, the computing platform may provide the one or more security questions and may validate one or more responses to the one or more security questions. Based on validating the one or more responses to the one or more security questions, the computing platform may provide user account information associated with the user account to the mobile device.

Abstract: Aspects of the disclosure relate to preventing unauthorized access to secured information systems. A computing platform may receive, from an end user desktop computing device, a request to login to a user account associated with a user account portal. In response to receiving the request, the computing platform may generate an authentication token in an authentication database and may send a notification to at least one registered device linked to the user account. After sending the notification, the computing platform may receive, from the at least one registered device, an authentication response message. If the authentication response message indicates that valid authentication input was received, the computing platform may update the authentication token to indicate that the request to login to the user account has been approved. After updating the authentication token, the computing platform may provide, to the end user desktop computing device, access to a portal interface.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems based on machine-learned user behavior profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account. The computing platform may capture behavioral parameters associated with the client computing device and may evaluate the behavioral parameters using a behavioral profile associated with the user account to determine a behavioral deviation score. Based on the behavioral deviation score, the computing platform may select an authentication action from a plurality of pre-defined authentication actions. Subsequently, the computing platform may generate commands directing an account portal computing platform to allow access, conditionally allow access, or prevent access based on the selected authentication action.

Abstract: Aspects of the disclosure relate to determining optimal machine learning models. A computing platform may collect, via a network, data indicative of login activity to an enterprise resource. One or more initial features indicative of the login activity may be identified. Based on the one or more initial features, an initial test dataset and a test model may be generated. Then, the test model may be deployed in a production environment. Subsequently, the computing platform may identify one or more production feature vectors. Then, the computing platform may generate, based on the one or more production feature vectors, a training dataset. Subsequently, the computing platform may perform, for the training dataset, a data quality check. Then, the computing platform may predict, by applying Bayesian optimization to the training dataset, an optimal machine learning model. Subsequently, the computing platform may apply the optimal machine learning model to detect unauthorized activity.

Abstract: Aspects of the disclosure relate to preventing unauthorized access to secured information systems. A computing platform may receive, from an end user desktop computing device, a request to login to a user account associated with a user account portal. In response to receiving the request, the computing platform may generate an authentication token in an authentication database and may send a notification to at least one registered device linked to the user account. After sending the notification, the computing platform may receive, from the at least one registered device, an authentication response message. If the authentication response message indicates that valid authentication input was received, the computing platform may update the authentication token to indicate that the request to login to the user account has been approved. After updating the authentication token, the computing platform may provide, to the end user desktop computing device, access to a portal interface.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems based on machine-learned user behavior profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account. The computing platform may capture behavioral parameters associated with the client computing device and may evaluate the behavioral parameters using a behavioral profile associated with the user account to determine a behavioral deviation score. Based on the behavioral deviation score, the computing platform may select an authentication action from a plurality of pre-defined authentication actions. Subsequently, the computing platform may generate commands directing an account portal computing platform to allow access, conditionally allow access, or prevent access based on the selected authentication action.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems based on machine-learned event profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account in a client portal session. The computing platform may capture one or more behavioral parameters and may generate one or more authentication prompts. Thereafter, the computing platform may receive one or more authentication prompt responses and may evaluate an event pattern. Based on evaluating the event pattern and validating the one or more authentication prompt responses, the computing platform may generate and send one or more authentication commands directing an account portal computing platform to allow access to the one or more secured information resources associated with the user account in the client portal session.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems using machine-learned user-account behavior profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account. The computing platform may capture one or more behavioral parameters and may authenticate the user of the client computing device to the user account based on the one or more behavioral parameters and one or more authentication credentials. The computing platform then may generate and send one or more authentication commands directing an account portal computing platform to allow access to the one or more secured information resources. Subsequently, the computing platform may capture activity data associated with one or more interactions in a client portal session and may update a behavioral profile associated with the user account.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems using machine-learned user-account behavior profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account. The computing platform may capture one or more behavioral parameters and activity data associated with one or more interactions with one or more non-authenticated pages. Then, the computing platform may evaluate the one or more behavioral parameters and the activity data using a behavioral profile associated with the user account. Based on this evaluation, the computing platform may identify the authentication request as malicious and may generate and send one or more denial-of-access commands to prevent the client computing device from accessing the one or more secured information resources associated with the user account.

Abstract: Aspects of the disclosure relate to preventing unauthorized access to secured information systems. A computing platform may receive, from an end user desktop computing device, a request to login to a user account associated with a user account portal. In response to receiving the request, the computing platform may generate an authentication token in an authentication database and may send a notification to at least one registered device linked to the user account. After sending the notification, the computing platform may receive, from the at least one registered device, an authentication response message. If the authentication response message indicates that valid authentication input was received, the computing platform may update the authentication token to indicate that the request to login to the user account has been approved. After updating the authentication token, the computing platform may provide, to the end user desktop computing device, access to a portal interface.

Abstract: Systems for detecting unauthorized user and controlling dynamic user interface functionality are provided. The system may receive a request to access functionality that may include login credentials of a user. The request may also include additional information associated with a computing device from which the request is received. The request and additional data may be analyzing using one or more machine learning datasets to determine whether a user requesting access is an authorized user or an unauthorized user. If the user is an authorized user, the user may be authenticated to the system an authentic user interface having enabled functionality may be generated. If the user is an unauthorized user, a decoy user interface having functionality disabled may be generated.

Abstract: Aspects of the disclosure relate to processing authentication requests to secured information systems using machine-learned user-account behavior profiles. A computing platform may receive an authentication request corresponding to a request for a user of a client computing device to access one or more secured information resources associated with a user account. The computing platform may capture one or more behavioral parameters and activity data associated with one or more interactions with one or more non-authenticated pages. Then, the computing platform may evaluate the one or more behavioral parameters and the activity data using a behavioral profile associated with the user account. Based on this evaluation, the computing platform may identify the authentication request as malicious and may generate and send one or more denial-of-access commands to prevent the client computing device from accessing the one or more secured information resources associated with the user account.

Abstract: Aspects of the disclosure relate to preventing unauthorized access to secured information systems. A computing platform may receive, from an end user desktop computing device, a request to login to a user account associated with a user account portal. In response to receiving the request, the computing platform may generate an authentication token in an authentication database and may send a notification to at least one registered device linked to the user account. After sending the notification, the computing platform may receive, from the at least one registered device, an authentication response message. If the authentication response message indicates that valid authentication input was received, the computing platform may update the authentication token to indicate that the request to login to the user account has been approved. After updating the authentication token, the computing platform may provide, to the end user desktop computing device, access to a portal interface.