Abstract: In some instances, a method is provided. The method comprises: generating a first subject identifier for the first domain, wherein the first subject identifier comprises a plurality of elements, wherein at least one of the plurality of elements comprises a subject identifier fragment indicating a unique identifier string for the user; based on a second user request to access second content for a second domain from the user device associated with the user, determining whether the user is enrolled into the subject identifier authentication; in response to determining that the user is enrolled into the subject identifier authentication for the first domain, generating a second subject identifier for the user for the second domain based on the subject identifier fragment from the first subject identifier for the first domain; and granting access to the second content for the second domain based on generating the second subject identifier.

Abstract: In some instances, a method for generating network traffic rules for a cloud environment is provided. The method comprises: converting a plurality of internet protocol (IP) addresses from a plurality of network traffic rules into a plurality of integer pair representations of the IP addresses; determining a plurality of similarity values based on the plurality of integer pair representations of the IP addresses and a similarity algorithm; determining stability of one or more of the plurality of network traffic rules based on the plurality of similarity values and one or more thresholds; and applying the one or more of the plurality of network traffic rules that are determined to be stable.

Abstract: In some instances, a method is provided. The method comprises obtaining one or more care gap machine learning-artificial intelligence (ML-AI) models; obtaining individual information of an individual, wherein the individual information indicates one or more medical conditions of the individual and personal information of the individual; determining care gap information of the individual based on using the one or more care gap ML-AI models and the individual information, wherein the care gap information indicates one or more predictions for expectancy of a care gap of the individual, and wherein the care gap is associated with a gap in time that the individual has a lapse in receiving medical care for the one or more medical conditions; and performing one or more care gap interventions based on the care gap information.

Abstract: A system and method are disclosed for monitoring health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In some embodiments, the input vector can also include social determinants data and/or demographic data. The output of the deep learning algorithms provides classifiers that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: In some instances, a method for generating security rules for a cloud environment is provided. The method comprises: generating one or more dictionary data structures based on a plurality of data logs, wherein each of the one or more dictionary data structures comprise a key and a value; determining one or more recent network traffic rules based on the one or more generated dictionary data structures; determining a new recommended network traffic rule based on one or more security groups associated with the plurality of data logs and consolidating the one or more recent network traffic rules with historical proposed traffic rules; and applying the new recommended network traffic rule to network data transferred between a server machine and one or more client machines.

Abstract: Systems and methods for automated summarization of customer service calls in a specialized field, such as medical services and insurance, are disclosed. Call transcripts are processed to determine the utterances and corresponding speakers in a customer service call. A feature vector is generated for each utterance and processed through a trained intent model to assign intent labels. The utterances are then filtered based on the intent labels to generate an extractive summary. The extractive summary is processed through a trained summarization model to generate a natural language summary for the customer service call.

Abstract: In some instances, a method is provided. The method comprises: obtaining, by a computing system, a plurality of documents, wherein at least one document, of the plurality of documents, comprises one or more circular shaped user indications, wherein each of the one or more circular shaped user indications indicates a user selection of a design or text within the associated circular shaped user indication; determining, by the computing system, circular shaped identification information for a document, of the plurality of documents based on inputting the document into a trained machine learning—artificial intelligence (ML-AI) model, wherein the circular shaped identification information indicates the user selection of the design or the text within the associated circular shaped user indication; and performing, by the computing system, one or more actions based on the circular shaped identification information.

Abstract: A system and method are disclosed for predicting short term health outcomes based on data collected by a wearable device such as an activity tracker or a smart watch. Artificial Intelligence (AI) algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In particular, a framework is defined that includes a random forest model configured to classify a user based on the monitored parameter data and embedding data. Based on a positive health outcome classification, a minimum value is assigned to a health index value for the user or, based on a negative health outcome classification, a gradient boosting machine is configured to generate the health index value. Various operations can be performed based on the assigned health index value for the user.

Abstract: A system comprising a first user device is provided. The first user device is configured to: obtain biometric registration data associated with a user; generate a secret key for the biometric registration data, wherein the secret key indicates an index translate point array; determine enrollment data for the user based on an index translate function, the biometric registration data, and the secret key, wherein the index translate function modifies entries of the biometric registration data based on the index translate point array; generate one or more cryptographic keys for the user based on the index translate point array; and provide, to a computing platform, ancillary information associated with the one or more cryptographic keys and the enrollment data.

Abstract: In some instances, a method for verifying communication paths is provided. The method comprises: obtaining, from a first user device, a request to access content associated with a relying party system, wherein the request indicates user credentials and a first session identifier (ID); obtaining one or more quick response (QR) codes and a second session ID associated with a first QR code of the one or more QR codes, wherein the relying party system generates and provides the first QR code to the first user device; and verifying the first session ID and the second session ID, wherein the relying party system grants the first user device access to the requested content based on the verification.

Abstract: A method for authenticating a user is provided. The method comprises: providing first biometric enrollment data of the user to a first enrollment system of a plurality of enrollment systems; receiving a first enrollment identifier identifying the first enrollment system; storing the first enrollment identifier identifying the first enrollment system into a digital wallet of the user; in response to a request to access content on a relying party system, providing a biometric marker of the user and the first enrollment identifier from the digital wallet of the user to the relying party system; based on the relying party system identifying the first enrollment system using the first enrollment identifier and verifying the biometric marker of the user with the first enrollment system, accessing the requested content associated with the relying party system.

Abstract: A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: Embodiments of the disclosure provide a method for enhancing standard authentication systems to include risk-based decisions. Risk-based decisions can be selectively implemented within existing authentication systems to strategically modify and supplement security if an unacceptable risk is detected. Embodiments capture information pertaining to a user and user device. Information is stored to create a profile for the user and user device. A comparison between the stored information and live data can be performed within authentication systems to optimize security. If the results of the comparison demonstrate the presence of an acceptable risk, then the need for subsequent authentication can be reduced or eliminated, which improves a user experience.

Abstract: In some instances, a method for verifying communication paths is provided. The method comprises: obtaining, from a first user device, a request to access content associated with a relying party system, wherein the request indicates user credentials and a first session identifier (ID); obtaining one or more quick response (QR) codes and a second session ID associated with a first QR code of the one or more QR codes, wherein the relying party system generates and provides the first QR code to the first user device; and verifying the first session ID and the second session ID, wherein the relying party system grants the first user device access to the requested content based on the verification.

Abstract: In some instances, a user device for determining whether an individual is sick is provided. The user device is configured to obtain a facial image of an individual; obtain an audio file comprising a voice recording of the individual; determine a facial recognition confidence value associated with whether the individual is sick based on inputting the facial image into a facial recognition machine learning dataset that is individualized for the individual; determine a voice recognition confidence value associated with whether the individual is sick based on inputting the audio file into a voice recognition machine learning dataset that is individualized for the individual; determine whether the individual is sick based on the facial recognition confidence value and the voice recognition confidence value; and causing display of a prompt indicating whether the individual is sick.

Abstract: A unified data fabric for controlling data lifecycles and data flows between trusted data sources and data clients is described herein. A system can include a data ingestion engine and a data delivery engine. The data ingestion engine and the data delivery engine are connected to a data lifecycle engine that maintains data control policies and access control policies. The data ingestion engine is configured to control ingestion of data elements into the unified data fabric based on the data control policies, and the data delivery engine is configured to control access to data elements in the unified data fabric based on access control policies. Each data element from one or more trusted data sources is associated with a global identifier to provide a comprehensive view of information about a constituent from a variety of disparate data sources.

Abstract: In some instances, the disclosure provides a method for identifying access anomalies using network graphs. The method comprises obtaining access data for an entity, generating a network graph baseline profile based on the plurality of data elements, generating a network graph current profile based on the plurality of data elements, generating comparison data based on comparing the plurality of baseline network graphs with the one or more current network graphs and comparing the plurality of baseline nodes and the plurality of baseline edges with the plurality of current nodes and the plurality of current edges, determining, based on the comparison data, anomaly data comprising one or more flagged network accesses to the enterprise system, and providing the anomaly data indicating the flagged network accesses to an authentication system.

Abstract: Methods and systems for analyzing care data are described. The method includes building a virtual model of a physical medical device. Training is provided to a patient associated with the physical medical device to properly use the physical medical device by manipulating the virtual model. First care data associated with a first sensor associated with the physical medical device and second care data associated with a second sensor is received by a cloud service. The cloud service analyzes the first care data to obtain a first care data score and analyzes the second care data to obtain a second care data score. The cloud service scores, using a machine learning algorithm, the first care data score and the second care data score to obtain a combined care score. The cloud service determines whether the combined care score is greater than a threshold. The cloud service triggers an emergency procedure when it is determined that the combined care score is greater than the threshold.

Abstract: In some instances, a method for authenticating a user using key pair authentication is provided. The method comprises enrolling the user into key pair authentication by generating a private and public key pair for an authentication domain, accessing the content on the first domain based on enrolling the user into the key pair authentication with a key pair authentication server using the private and public key pair for the authentication domain, requesting access for different content on a second domain, based on enrolling the user into the key pair authentication for the first domain, redirecting a browser from the second domain to the authentication domain, and accessing the different content on the second domain based on performing the key pair authentication with the key pair authentication server using the private and public key pair for the authentication domain.