22 results about "Service infrastructure" patented technology

Infrastructure for zero trust network access (ZTNA) is deployed as a cloud-based service remotely from a customer premises where user applications are hosted. By connecting an appliance on the customer premises to the cloud-based service through a secure tunnel or the like, an application hosted on the customer premises can then be accessed externally as a ZTNA application without the customer premises opening a firewall to public networks or otherwise exposing potential attack surfaces to the customer premises.

The control device has a UID, which it supplies to the service infrastructure. A vehicle data set, containing the UID, of the vehicle is known and accessible via a backend service of the vehicle manufacturer. A user enters into a service contract for a service with a service provider via a software interface of an application by the backend service. The control device supplies the UID to the service infrastructure as a reference or as a hashID created temporarily by means of a time-based one-time password algorithm. The UID is read out during production of the vehicle via a diagnostic service and is permanently stored in the vehicle data set of the vehicle. The backend service determines the UID of the control device installed in the vehicle, required for entering into the service contract, from the vehicle data set and automatically adopts it.

The present disclosure relates to systems and methods for providing a network-based service infrastructure configuration for a plurality of network-based services. A configuration service may identify one or more network-based services based on identifying the customer's profile and grouping the customer with other customers having a similar profile. After grouping the customer input, the configuration service may automatically provide network infrastructure configuration templates. The configuration service may identify and verify attributes required by each identified service and its associated property values. The configuration service may configure the infrastructure configuration by selecting a template from the plurality of templates stored in a datastore.

To provide a mobility service providing system, a vehicle access control method, and a program.SOLUTION: In a method, when an interface unit (API providing unit 122) receives, from a service providing server 4 that provides a service to a vehicle using a mobility service infrastructure server (management center 3), an access request for requesting an operation of an in-vehicle device with respect to the vehicle, access to a target vehicle is executed by performing wireless communication with an in-vehicle device mounted on the target vehicle which is a vehicle to be accessed. A vehicle control unit 130 of a vehicle-side unit 110 performs relay control on a control instruction transmitted and received to and from the in-vehicle device.SELECTED DRAWING: Figure 11

Techniques for a head-end node in one or more network autonomous systems to utilize a protocol to instantiate services on tail-end nodes. The head-end node can use a service request mechanism that is enabled by the protocol to request service instantiation on the tail-end node without a network operator having to manually configure the tail-end node, or even having access to the tail-end node. Additionally, the protocol may provide mechanisms to define handling attributes for traffic of the service (e.g., quality of service (QoS) attributes, Maximum Transmission Unit (MTU) settings, etc.), service acknowledgement mechanisms for the head-end node to determine that the service was instantiated on the tail-end node, and so forth. In this way, a head-end node can be used to instantiate a service on a tail-end node without a network operator having to have direct access to the tail-end node to manually configure the tail-end node.

An information processing device according to one embodiment includes: a reception means that receives an API request containing user identification information of a user and service identification information indicating a service from a service infrastructure that provides the service to the user via a whole-body scanner; a first acquisition means that acquires, via a first access means, whole-body data of a category indicated by a first database as being used in the service indicated by the service identification information included in the API request from among whole-body data of the user indicated by the user identification information included in the API request; a second acquisition means that acquires, via a second access means, UI data for displaying, on the whole-body scanner, a menu for the whole-body scanner to provide the service indicated by the service identification information included in the API request; and a transmission means that transmits, to the service infrastructure, an API response including the whole-body data acquired by the first acquisition means and the UI data acquired by the second acquisition means.

A computer-implemented security architecture prevents compromise of an artificial-intelligence workload, agent, model-orchestration platform, or application server from automatically becoming an enterprise-wide data breach, unrestricted semantic reconstruction, strategic-intelligence extraction, unauthorized cross-domain correlation, or unauthorized externally effective operation. Enterprise information is partitioned among independently controlled identity, content, relationship- mapping, and optional cryptographic-material domains such that protected components remain Technically Non-Joinable outside an authorized reconstruction session. A non-bearer Reconstruction Authorization Object (RAO) binds permitted fields, permitted association scope, authorized purpose, execution context, attested workload identity, tenant, session, policy epoch, jurisdiction, recipient, destination, disclosure conditions, and output scope to protected authorization state. Approved components are released as session-bound components and reconstructed only within a Protected Reconstruction Domain to create an ephemeral minimum-necessary representation without persistently reconstructing a complete semantically usable enterprise record outside the protected processing span. Where an artificial-intelligence server, autonomous agent, retrieval pipeline, model-orchestration framework, tool-use environment, vector-store interface, or application server is compromised, an attacker may attempt to reconstruct customer data, financial records, research assets, source code, intellectual property, product-development information, communications, operational intelligence, or strategic enterprise relationships. However, compromise of computation does not itself provide reconstruction authority, semantic association authority, or Release Authority. Generated Candidate Acts and Candidate Outputs remain sealed, capability-restricted, confined to protected state, or otherwise Non-Releasable while current execution-context correspondence, provenance continuity, permitted association scope, revocation state, policy epoch, destination, recipient, disclosure budget, inference-channel budget, and jurisdiction conditions are independently verified. A Protected Output Validation Receipt is committed before an output-specific Output Release Capability is generated, such that only a designated Output Release Boundary can render, transmit, invoke, store, commit, execute, or otherwise effectuate the verified result. The disclosed architecture establishes Execution–Consequence Decoupling, Mandatory Mediation, Technical Non-Joinability, and Technical Non-Completability, enabling enterprise artificial intelligence to compute without independently acquiring authority to disclose protected enterprise relationships or produce unauthorized external consequences. The architecture is applicable to enterprise AI, agentic AI, multi-agent systems, model-serving infrastructure, retrieval-augmented generation, vector databases, cloud computing, confidential computing, cybersecurity, telecommunications, financial services, healthcare, government systems, industrial automation, critical infrastructure, robotics, autonomous systems, and cyber-physical environments.

A method and system for an application programming interface (API) based container service for supporting multiple machine learning (ML) applications is described. In particular, a scoring service container includes a base scorer to interface with a ML serving infrastructure using the API. The scoring service container also includes an application specific scorer, which itself includes a model loader and a scoring function. A model identifier is provided to the model loader, and it provides a model object. At least some parameters in a request from a client application are passed to the scoring function, which produces a scoring. The base scorer returns the scoring according to the API to the ML serving infrastructure for delivery to the client application.

The invention provides a student data desensitization method, device and system and a storage medium, and belongs to the technical field of data desensitization, and the method comprises the steps: importing an original student information image and a student name list; performing correction analysis on the original student information image to obtain a corrected student information image; segmenting the corrected student information image to obtain a text feature image and a table structure image; performing coordinate analysis on the character feature image according to the student name list to obtain a target coordinate vector set; according to the method, the desensitization efficiency and accuracy are greatly improved, digital service infrastructures of different scenes can be compatible, leakage of irrelevant sensitive information is avoided, the problems of low efficiency, high error rate, privacy leakage risk and the like in traditional manual processing are effectively solved, and reliable technical guarantee is provided for safe sharing of education data.

A method for constructing an infrastructure as code is provided. The method comprises: inputting security information about a target service into a language model; using information output from the language model, so as to generate a security policy corresponding to the security information; inputting the security policy into the language model; using information output from the language model, so as to acquire attribute information about the target service and a first code script corresponding to the security policy; inputting the attribute information and the first code script into the language model; using information output from the language model, so as to generate a second code script for constructing an infrastructure of the target service; and using the second code script so as to automatically construct the infrastructure for providing the target service.

A workload management system monitors a tenant-specific workload for a tenant on a first set of cloud service instances hosted by a first cloud services infrastructure at a first cloud service location. The workload management system determines that a second cloud service location can host a predicted tenant-specific workload. The system obtains weather data for the cloud service locations. Based at least in part on the predicted tenant-specific workload and the weather data for the cloud service locations, the workload management system determines non-carbon costs of hosting and / or migrating the predicted tenant-specific workload while maintaining baseline performance criteria and a carbon cost of hosting and / or migrating. Based at least in part on the calculated costs, the system stores an indication that carbon emissions will be reduced by hosting the predicted tenant-specific workload at the second cloud service location and routes an ongoing workload to the second cloud service location.

The invention relates to the field of public service infrastructure inspection, and particularly discloses a public service inspection mileage positioning method and system, and the method comprises the following steps: S1, obtaining mileage basic information; s2, displacement information and angular displacement information are obtained, so that the mileage basic information is corrected for the first time; s3, correcting the mileage basic information for the second time on the basis of a ballast bed electronic tag; s4, capturing and counting fixed features of the outer side of the steel rail based on a video stream, and correcting the mileage basic information for the third time; s5, performing fourth correction on the mileage basic information based on a positioning kilometer post of a tunnel wall; wherein the steps from S1 to S5 are executed when the inspection equipment runs on the track line. According to the system, data of various sensors such as a wheel built-in encoder, a digital inertial navigation module, an inspection camera, a visual monitoring camera and a tunnel inspection camera are combined, so that multi-source data are collaboratively fused, and a mileage measurement result is more accurate.

This invention provides a method and apparatus for recursive resolution and resource allocation of computing power identifiers based on the Domain Name System (DNS). Based on the DNS service infrastructure, it supports the resolution and addressing of wide area network (WAN) computing power identifiers using the DNS, offering higher reliability, security, and stability compared to newly built identifier systems. Based on DNS service nodes, it can simultaneously resolve computing power resources and allocate and schedule computing power demands during identifier resolution, efficiently utilizing computing power resources and achieving computing-network convergence. The top-down resolution and resource allocation method from the root node facilitates macro-control and allocation of computing power resources within and between WANs, enabling balanced service of computing power resources at the network level to improve the overall service performance of the computing power network.

The present invention provides a cloud service honeypot generation method and system for active defense, which relates to the field of network security technology, including: generating a cloud asset map based on initial honeypots and honeypot deception scenarios obtained by simulating real asset devices; obtaining an updated cloud asset map when an authenticated user drags and changes a cloud function, exporting a configuration file based on the updated cloud asset map, and extracting template samples from a preset honeypot policy template library based on the configuration file; arranging the template samples to obtain multiple honeypot deployment templates that conform to the corresponding cloud environment and attack path; generating multiple IaC source code files based on an IaC template, and calling a preset Terraform based on the IaC source code files to generate multiple honeypots. The present invention adopts a completely real cloud service infrastructure as a honeypot, utilizes the design concept of input parameters, output parameters, and intermediate checkpoints in the honeypot, and cooperates with the monitoring and alarm of the cloud service itself to adjust the honeypot in real time, thereby improving the security of the network system.

The invention relates to the technical field of software network online upgrading, and discloses a method and a system for remotely controlling upgrading of an audio processor based on a web terminal. The method for upgrading the audio processor is applied to a Web interactive terminal and specifically comprises the following steps: S101, after receiving a system starting signal of the audio processor, automatically initializing and operating an embedded HTTP server application, continuously monitoring a preset port, establishing a network communication service infrastructure and loading a security protocol module; according to the method, it is ensured that the upgrading service is continuously available in various network environments, even if a high-load audio task runs, the QoS module can still ensure that an upgrading channel is smooth, the upgrading failure rate caused by network interruption due to breakpoint resume and cross validation is reduced, meanwhile, data packet loss is effectively avoided through the double-buffer storage design, and the upgrading efficiency is improved. The four-level verification process is combined with hardware-level digital signature verification, malicious firmware injection attacks can be intercepted, and an end-to-end trusted chain from transmission to execution is constructed.

Globally our environment comprises structures built to perform a meet different requirements including residential, commercial, retail, recreational and service infrastructure. Whilst, millions of tons of construction materials are deployed annually the quality control procedures in many instances have not changed to reflect today's demands. Accordingly, it would be beneficial to provide construction companies, engineering companies, infrastructure owners, regulators, etc. with means to automated testing / characterization of construction materials during at least one of its manufacture, deployment in construction and subsequent infrastructure life. It would be further beneficial for such automated methods to exploit self-contained data acquisition / logging modules allowing them to be employed with ease at the different points in the life cycle of a construction material and / or construction project.

An edge computing service-providing method and an apparatus for the same are disclosed. An infrastructure information apparatus for an edge computing service located in a control plane of a mobile communication network comprises an API server that receives a user plane function (UPF) selection request message from a session management function (SMF) of the mobile communication network when there is an edge computing service request from a user equipment (UE), a local database that stores at least one of a plurality of service names, a plurality of service identifiers corresponding to the plurality of service names, a plurality of MEC (multi-access edge computing) server identifiers, resource status information for each of the plurality of MEC servers, a UPF identifier for connection to each of the plurality of MEC servers, and a user terminal identifier connected to each of the plurality of MEC servers, and an analyzer that selects an optimal MEC server for providing the requested edge computing service through information stored in the local database or through query and response with an information system in a cloud computing infrastructure or Internet infrastructure, wherein the API server transmits a response message including a UPF identifier for connection to the selected optimal MEC server to the SMF.

The application provides a computing network service basic unit construction system, method, electronic equipment and storage medium, belongs to the technical field of computing network, and the system comprises a resource aggregation module, a data fusion module, a model training module and an ability opening module. The computing network service basic unit construction system provided by the application realizes the access and unified management of multi-source information technology resources through the resource aggregation module; the data fusion module is used for fusing multiple resource management data to obtain multiple fusion data; the model training module is used for training artificial intelligence based on the multiple fusion data to obtain multiple large models; and the ability opening module is used for opening the multiple large models to external users. The combination of the four modules can improve the resource utilization, data fusion degree and model training efficiency in the information technology construction and operation mode, provide better computing network service ability for the industry and the industry, and effectively promote the digital transformation of the industry and the industry.

The present disclosure relates to managing resource utilization in cloud service infrastructure. A device can monitor the cloud service. The cloud service can be configured with an automatic scaling function based on a threshold. The device can determine, based on the monitoring, that a utilization value of the cloud service during a time interval exceeds the threshold. The device can generate, using a policy based on the utilization value and the threshold, an instruction to disable the automatic scaling function of the cloud service by the one or more servers. The device can transmit the instruction to the one or more servers via a second cloud application programming interface. The device can generate, responsive to the policy, a service ticket data structure with an indication of the utilization value and the time interval. The device can provide the service ticket data structure to an electronic board.

Described techniques implement a bottom-up approach to implementing and scaling a plurality of deployed monitoring agents in a cluster of agents. Each of a plurality of monitoring agents may discover system resources to be monitored, and each monitoring agent may determine its capability, if any, of collecting related monitoring data. Each monitoring agent may then request permission or authorization to commence related monitoring. Centralized management may be provided that provides authorization or denial decisions to each deployed agent that requests such authorization to collect and report on specific instances of monitored entities. Accordingly, centralized decision making may be provided that does not require centralized, top-down load balancing.