138 results about "Enterprise computing" patented technology

Disclosed are techniques for using machine learning models to more reliably predict likelihoods of application failure. A model is trained to identify and display events that may cause high severity application failures. Logistic regression may be used to fit the model such that application features are mapped to a high severity event flag. Significant features of applications that relate to the high severity flag may be selected using stepwise regression. The identified applications may be displayed on a graphical user interface for review and reprioritization. Information may be ranked and displayed according to multiple different ranking criteria, such as one ranking generated by a first model, and another determined by one or more users. The multiple ranking criteria may be used to inform steps taken, and / or to retrain or tune the parameters of the model for subsequent predictions or classifications.

A system and method for the dynamic authentication revocation using privilege assurance of enterprise computer network environments using lateral movement detection and prevention. The system uses local session monitors to monitor logon sessions within a network, generating and verifying event logs and authentication records to ensure the legitimacy of authenticated user sessions and to revoke credentials when an illicit session is detected and further removing potentially compromised network components from the network, halting lateral movement in real-time.

Systems and methods are provided for agentless attestation. Agentless attestation can measure the integrity of customer servers without requiring an agent software program to be downloaded to each of the enterprise computer devices. In particular, the system can integrate several standalone components to measure the integrity of monitored devices. This also allows the data center to authenticate, verify, audit, and update any hardware change, including a Platform Certificate.

Various aspects of the disclosure relate to enforcing dynamically updated network security policies in real-time (or upon an identified update) from multiple organizations and anonymously analyze computing system configuration information uploaded from third-party computing systems. An analysis engine monitors compliance information and compare the compliance information against the security rules and / or requirements for one or more enterprise networks. A visualization providing a network map with a visual representation of each product system service system may include communication links between internal applications and / or computing systems and drill-down capability to identify issues as they are occurring or are predicted to occur. The security escrow system may include a mechanism to automatically enable / disable access between third party networks and one or more enterprise computing systems in real-time based on identified compliance information.

Examples are disclosed related to using verification channels for end-user verification. One example provides a method comprising, in a first verification channel, receiving a first verification request and an end-user mobile number from an enterprise computing system, sending a first-time sign-in request to an end-user computing device, and receiving a first end-user authentication message in response to the first-time sign-in request, and in response, associating a passkey with the end-user mobile number. The method further comprises, in a second verification channel, receiving a second verification request and the end-user mobile number from the enterprise computing system, sending a sign-in message, receiving a second end-user authentication message in response to the sign-in message, and in response to receiving a verification approved response from the end-user computing device, sending the verification approved response to the end-user computing device and / or the enterprise computing system.

The invention relates to the technical field of computing power resource sharing in a data center application environment, and discloses an enterprise computing power layout and intelligent decision mobile application system and an implementation method thereof. And real-time monitoring and dynamic scheduling of internal or cloud computing resources of an enterprise are realized. Historical data and real-time load are processed by using machine learning and an optimization algorithm, an optimal scheduling scheme is generated, and an alarm is automatically triggered when abnormality is detected, so that efficient utilization of enterprise resources is ensured. The method has the advantages of being high in real-time performance, intelligent, flexible in expansion, safe, reliable and the like, and the operation and maintenance efficiency and decision response speed of enterprises can be remarkably improved.

Systems and methods for an enterprise computing platform may include a server that may include a desktop-as-a-service module, a user behavior analytics module, a remote monitoring and management module, an analytics-as-a-service module, an insider threat prevention and monitoring module, and a project tracker module. The server or modules may provide remote desktop sessions in an efficient and convenient manner, may analyze user behavior and automatically execute corrective actions in response to rules violations, and may monitor and manage multiple computer systems and computing sessions as to their statuses, versions, authentication, or compliance.

A system and method for the privilege assurance of enterprise computer network environments using attack path detection and prediction. The system uses local session monitors to monitor logon sessions within a network, track session details, and log session and network host details. Cyber-physical graphs are produced and used to identify paths within the network based on the logged information, and to apply risk weighting to the identified paths and determine likely attack paths an attacker may use.

An agent deployment system for adaptively managing artificial intelligence agents within an enterprise computing environment. The system can include an agent subsystem having a control agent configured to receive source data from one or more data sources of the enterprise, continuously monitor the source data for an occurrence of a trigger event indicative of a condition requiring an AI based intervention, detect the trigger event, evaluate the trigger event to identify a relevant operational context, and then based on the trigger event and the operational context, select and deploy the plurality of AI agents from a total set of AI agents to address the trigger event by performing an AI-based intervention.

A computer-implemented system and method for evaluating an AI agent associated with an enterprise computing environment by aggregating a plurality of AI agents associated with the enterprise computing environment, and evaluating, with an agent evaluation unit, a selected AI agent of the plurality of AI agents using evaluation data, wherein the evaluation data includes operational behavior data and trustworthiness data. The agent evaluation unit can be configured to determine a total agent evaluation score for the selected AI agent from a plurality of category specific evaluation scores. The agent specific categories can have associated therewith a category evaluation score and the agent specific categories can include categories associated with the operational behavior and the trustworthiness of the selected AI agent. An AI-based intervention can be applied in response to the total agent evaluation score.

The invention discloses an industrial chain generation method and system based on big data, and the method comprises the steps: designing a main structure of an industrial chain and a keyword table of each node, and determining the classification of the upstream, the middle and the downstream of the industrial chain, including a main node, a child node, a branch node, a name of each node and a keyword contained in the node; multi-dimensional industrial data such as industry and commerce data, bidding and tendering, public opinions, patents and software aboriginal information of enterprises are collected and acquired, and an enterprise basic database is established; primary screening of the uplink enterprises: screening the enterprises from the enterprise basic database according to the industrial chain node keywords, and incorporating the enterprises into an alternative uplink enterprise database; the enterprise upper chain evaluation index system is used for evaluating the matching degree between dimension information such as the business scope, the technical achievement, the public opinion information and the bidding and tendering of the enterprise and the industrial chain node; selecting each node benchmark enterprise on an industrial chain according to industrial research, and calculating each uplink index of each benchmark enterprise; calculating a vector distance between the primarily screened selected enterprise and the benchmarking enterprise; ranking the similarity calculation results in a descending order; according to the Pareto's law, the first 20% of enterprises are taken to be linked, and a complete industrial chain is constructed. The method comprises the following steps: collecting enterprise multi-dimensional data, constructing an industrial chain main body structure and each node keyword, screening to-be-linked enterprises according to keywords, establishing an uplink evaluation index system, calculating vector distances between the to-be-linked enterprises and benchmarking enterprises, and determining an uplink enterprise mode according to vector distance ranking to generate an industrial chain. The method is beneficial for improving the accuracy and efficiency of industrial chain generation, so that reference basis is provided for scientifically evaluating the industrial development level, making investment decisions of industrial development, making effective industrial policies and the like.

A system associated with an enterprise computing environment infrastructure may include a chaos testing tool data store that contains a plurality of electronic records, each record including a chaos engineering fault parameter. A computer processor of a chaos testing tool may receive, from a chaos testing user, injection information associated with an element of the enterprise computing environment infrastructure. The chaos testing tool may then access the chaos engineering fault parameter from the chaos testing tool data store and automatically arrange to inject a chaos engineering fault into operation of the element of the enterprise computing environment infrastructure in accordance with the injection information and the chaos fault parameter. A response of the element of the enterprise computing environment infrastructure may then be measured subsequent to said injection, and the system may output an indication of the measured response to the chaos testing user.

The invention provides an ocean and related industry classification and identification method and system. The method comprises the following steps: S1, establishing an enterprise credit information database; s2, acquiring a standard file, and performing text preprocessing on the standard file and the manual identification sample; s3, establishing a sea-related enterprise identification model according to an artificial identification sample and the standard file; s4, identifying the to-be-identified enterprise by using the sea-related enterprise identification model to obtain a model identification sample, and calculating the identification accuracy and the extra identification ratio of each marine industry by comparing the model identification sample with the artificial identification sample; s5, adjusting the sea-related enterprise identification model, and identifying the to-be-identified enterprise by using the adjusted sea-related enterprise identification model to obtain an enterprise classification result; and S6, calculating an evaluation score of each identified marine industry for the enterprises in the enterprise classification result. The method can improve the accuracy of the recognition result, has interpretability, and can display the classification basis.

Various aspects of the disclosure relate to enforcing dynamically updated network security policies in real-time (or upon an identified update) from multiple organizations and anonymously analyze computing system configuration information uploaded from third-party computing systems. An analysis engine monitors compliance information and compare the compliance information against the security rules and / or requirements for one or more enterprise networks. A visualization providing a network map with a visual representation of each product system service system may include communication links between internal applications and / or computing systems and drill-down capability to identify issues as they are occurring or are predicted to occur. The security escrow system may include a mechanism to automatically enable / disable access between third party networks and one or more enterprise computing systems in real-time based on identified compliance information.

A system and method for the dynamic authentication revocation using privilege assurance of enterprise computer network environments using lateral movement detection and prevention. The system uses local session monitors to monitor logon sessions within a network, generating and verifying event logs and authentication records to ensure the legitimacy of authenticated user sessions and to revoke credentials when an illicit session is detected and further removing potentially compromised network components from the network, halting lateral movement in real-time.

An enterprise engineering and configuration system includes a common configuration database and support services stored in and executed in a compute fabric of an enterprise. The configuration database and support services use and implement a common configuration data schema to support the configuration of hardware and software in the compute fabric and at multiple different sites or physical locations of the enterprise even when different control and automation systems are used at these different sites or physical locations. The configuration system enables implementing hardware or software configuration changes to various different sites or locations of an enterprise either centrally from a configuration device connected directly to the compute fabric of the enterprise or locally from any physical location or site of the enterprise, while maintaining a single integrated enterprise configuration database that stores configuration data for each of the multiple sites of the enterprise. This configuration system is flexible as it enables engineering and configuration changes to be made by users anywhere in the enterprise for any of the sites of the enterprise and across different sites of the enterprise.

A. method of application modernization engine executed by processors. The application modernization engine provides improved application development through simulated intelligence and expanded tooling. The method includes determining, by the application modernization engine, a collection of resources to support a first functionality within an existing enterprise computer system and provide a set of outcomes. The method includes developing, by the application modernization engine, an application including the collection of resources with no-code and full-code operations. The method includes augmenting, by the application modernization engine, the application with a second functionality not present in the existing enterprise computer system. The method includes deploying, by the application modernization engine, the application into the existing enterprise computer system.

In accordance with various embodiments, described herein is a system and method for providing a traceable push-based pipeline and monitoring of data quality in extract, transform, load or other enterprise computing environments. The system can include a combination of features including one or more of: an end-to-end push-based pipeline, which uses task-based events to trigger downstream jobs; the application of a table-of-tables or control table, by which the system can trace with detail the performance of each task and corresponding data table changes; a decoupling of pipeline components across several dimensions, for example: task, data, role, and / or time; a user interface or dashboard for monitoring pipeline health or data quality over the pipeline components and dimensions; and an orchestrator that can learn from pipeline health data and task / table changes, and identify actual or potential issues involving the pipeline, including associated root causes.

Systems and methods are provided for agentless attestation. Agentless attestation can measure the integrity of customer servers without requiring an agent software program to be downloaded to each of the enterprise computer devices. In particular, the system can integrate several standalone components to measure the integrity of monitored devices. This also allows the data center to authenticate, verify, audit, and update any hardware change, including a Platform Certificate.

Disclosed are techniques for using machine learning models to more reliably predict likelihoods of application failure. A model is trained to identify and display events that may cause high severity application failures. Logistic regression may be used to fit the model such that application features are mapped to a high severity event flag. Significant features of applications that relate to the high severity flag may be selected using stepwise regression. The identified applications may be displayed on a graphical user interface for review and reprioritization. Information may be ranked and displayed according to multiple different ranking criteria, such as one ranking generated by a first model, and another determined by one or more users. The multiple ranking criteria may be used to inform steps taken, and / or to retrain or tune the parameters of the model for subsequent predictions or classifications.

Various embodiments relate generally to data science and data analysis, computer software and systems, and computing architectures and data models configured to facilitate management and performance of enterprise functions, and, more specifically, to an enterprise computing and data processing platform configured to implement applications and computerized tools configured to facilitate implementation of an enterprise data model to generate and manage component data objects representing enterprise tasks and processes, as well as portions thereof, any of which may be used to create and modify an enterprise data flow or a process flow, for example, using an enterprise computerized tool. In some examples, a method includes activating one or more applications as computerized tools to access subsets of one or more permissions, identifying an enterprise function data object to generate a third subset of permissions.

A method of application modernization engine executed by processors. The application modernization engine provides an improved contextual document processing and specific information extraction. The method includes receiving, by document intelligence sub-system of the application modernization engine, data of an enterprise computer system generated by artificial intelligence agents. The method includes processing, by the document intelligence sub-system, the data by extracting and ingesting specific contextual information to achieve document classification and feature extraction. The method includes providing, by the document intelligence sub-system, the specific contextual information, the document classification, and the feature extraction to the artificial intelligence agents to implement processes on top of the existing enterprise computer system to achieve objectives.

A system and method for the privilege assurance of enterprise computer network environments using lateral movement detection and prevention. The system uses local session monitors to monitor logon sessions within a network, generating and verifying event logs and authentication records to ensure the legitimacy of authenticated user sessions and to revoke credentials when an illicit session is detected, halting lateral movement in real-time.

Embodiments of systems and methods disclosed herein provide an application development platform in an enterprise computing environment. More specifically, in certain embodiments, systems and methods are disclosed that enable an application development platform to reuse, extend, and / or customize entity-based applications in an enterprise computing environment. The application development platform can extend an entity to include user configured settings including zero or at least one of a property, a permission, an action, a behavior, or a resource to the entity to generate user customized versions of the entity. The applications may be customized by an end user, while allowing the underlying application to be updated without losing any user customizations.

In accordance with various embodiments, described herein is a system and method for providing a traceable push-based pipeline and monitoring of data quality in extract, transform, load or other enterprise computing environments. The system can include a combination of features including one or more of: an end-to-end push-based pipeline, which uses task-based events to trigger downstream jobs; the application of a table-of-tables or control table, by which the system can trace with detail the performance of each task and corresponding data table changes; a decoupling of pipeline components across several dimensions, for example: task, data, role, and / or time; a user interface or dashboard for monitoring pipeline health or data quality over the pipeline components and dimensions; and an orchestrator that can learn from pipeline health data and task / table changes, and identify actual or potential issues involving the pipeline, including associated root causes.

A document capture server receives a document image from a document capture client and processes the image into an electronic document containing textual content. During capture, the document capture server determines a graphical layout of the document, extracts keywords from the document, classifies the document accordingly, and calls an artificial intelligence (AI) platform to gain insights on the textual content. The AI platform analyzes the textual content and returns additional, insightful data such as a sentiment of the textual content. The document capture server can validate the additional data, integrate the additional data in a process or workflow, and / or provide the textual content and the additional data to a content repository or a computing facility operating in an enterprise computing environment. The document capture server can provide validated data to the AI platform to improve future analyses by the AI platform.

Aspects of the disclosure relate to machine learning models and knowledge graphs. A computing platform may receive event processing data. Using a machine learning mode, the computing platform may identify k nearest data points corresponding to the event processing data. Using a knowledge graph, the computing platform may identify k nearest data nodes corresponding to the event processing data. The computing platform may generate first weighted relative distances between the event processing data and the k nearest data points, and second weighted relative distances between the event processing data and the k nearest data nodes. Based on the weighted relative distances, the computing platform may identify a data cluster for the event processing data. The computing platform may send, based on the identified data cluster, event processing information and one or more commands directing an enterprise computing device to display the event processing information.

A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.

A method and system for synchronizing secrets in an enterprise computing network include a secret and a representation of a directed acyclic graph (DAG) generated at a secret client vault device. The representation of the DAG having a plurality of nodes and a plurality of edges, the plurality of nodes including a record node associated with the record, a leaf node associated with a second secret vault client device, and one or more intermediate nodes and the plurality of edges specify a traversal path from the record node to the leaf node. Transmitting a data stream to the second secret vault client device that comprises multiply encrypted data generated in accordance with a traversal of the representation of DAG and representations of the encryption keys associated with the record node and the one or more intermediate nodes of the DAG traversed to generate the multiply encrypted data.

Computer-implemented systems and methods provision a virtual machine sandbox for evaluating software. Firewall means are provisioned for a cloud network to permit access to an internet site from which source code is downloadable. A client computer device, via virtualization, controls a virtual machine. The client computer device is on an on-premises network that is different from, and in communication with, the cloud network. The virtual machine is controlled to: (a) download to the virtual machine, via the firewall means, the source code from the internet site; and (b) execute the source code for evaluation of the source code. The virtual machine is deleted after a predetermined time period. The source code is prohibited, after provisioning the virtual machine and through deletion of it, from being downloaded from the virtual machine to computer devices on the on-premises network.