279 results about "System administrator" patented technology

The invention discloses an intelligent management method and system for IT equipment asset maintenance, and relates to the technical field of intelligent management. During system operation, multi-dimensional parameters of IT equipment are collected in real time and transmitted to a data processing module, the collected data are preprocessed, the current state of the equipment is comprehensively analyzed, and the health state coefficient Hstate of the equipment is calculated; the method comprises the following steps: acquiring a current equipment operation state, performing baseline establishment on historical operation data of the equipment, comparing the current state with the historical data, analyzing the performance trend and change of the equipment, calculating to obtain a trend analysis coefficient Ttend, and identifying potential problems and performance reduction trend of the equipment through long-term data accumulation. And calculating a final fault prediction probability index Pfault, comparing the final fault prediction probability index Pfault with a set threshold value, obtaining a grade prediction scheme, generating early warning information, prompting a system administrator to sort and distribute according to the urgency and priority of tasks, automatically generating a comprehensive report by the system, and providing decision support for the administrator.

XCB poly-radio devices as finders, locators, scanners, sensors, and Bluetooth (BT) radio topology reporters as part of a global lost-and-found services system. XCB devices function as “smart objects” and combine dual transceivers operating in the telecommunications and the low power ISM radio spectra, with default power management overrides under local control of the BT modem. “Familiar zones” are defined, and a “familiarity index” versus a “strangeness index” based on meta-analysis of BT radio contact logs are used to assign location. Location, in concert with other sensor data, is coupled to conditional logic rules programmable by the user or the system administrator. Locations, determined by monitoring familiar and unfamiliar BT radio topology, trigger executable commands to smartphones, to smart devices generally, and to remote machines, and can for example, generate alerts to a user if radiotagged assets, children or pets have strayed, are lost, or are left behind. When tied to cloud predictive services or increased edge computing capacity, incipient loss of radiotag objects can be detected before an owner knows the smart object is lost. In another embodiment, XCB devices having a novel chip architecture for improved power management of cellular and MCU circuits mediated by BT radio modem that achieves “situational awareness” by monitoring the BT signal environment around the device.

A computerized method is disclosed that includes operations of obtaining network traffic data between a source device and a destination device, applying a set of one or more security rules to a plurality of metrics of the network traffic data to obtain a subset of network traffic metrics, applying a first trained machine learning model to the subset of network traffic metrics to generate a feature vector through feature extraction of the subset of network traffic metrics, and evaluate the feature vector for a presence of beaconing and classify the subset of network traffic metrics, and responsive to the classifying of the subset of network traffic metrics, generating a flag for a system administrator. The plurality of metrics include at least one or more of packet size, packet transmission rate, or a ratio of (i) packet size for inbound packets and (ii) packet size for outbound packets.

An intelligent system for the joint detection of anomalies in distributed systems, comprising the following: an anomaly detection module deployed on distributed nodes, with each agent configured to monitor local system metrics, detect deviations from expected behavior, and identify potential anomalies using machine learning models; a collaborative learning machine that can be operated to facilitate peer-to-peer communication between the anomaly detection module, with the module working together to verify detected anomalies and correlate cross-node behaviors in real time; a centralized aggregation server configured to aggregate anomaly data from the distributed nodes, update a global anomaly detection model, and redistribute the updated model to each of the anomaly detection modules; a federated learning module configured to enable secure data exchange between distributed nodes without disclosing sensitive data, exchanging only updates to the machine learning model to protect privacy; a warning and mitigation module configured to send real-time alerts to system administrators or automated incident response systems when an anomaly is detected; categorizes alerts by severity and initiates automatic mitigation protocols to address critical threats; a self-learning and adaptation module capable of continuously updating local and global machine learning models, learning from past anomalies to detect emerging threats, and adjusting detection thresholds based on evolving threat landscapes; the global anomaly detection model refines local detection capabilities by incorporating insights from system-wide anomaly data across all nodes.

Systems and methods are disclosed that are directed to improving the prioritization, display, and viewing of system alerts through the use of machine learning techniques to group the alerts and further to prioritize the groupings. Additionally, a graphical user interface is generated that illustrates the prioritized listing of the plurality of groupings. Thus, a system administrator or other user receives an improved experience as the number of notifications provided to the system administrator are reduced due to the grouping of individual alerts into related groupings and further due to the prioritization of the groupings. Previously, or in current technology, system alerts may be automatically generated and provided immediately to a system administrator. In some instances, any advantage of detecting system errors or system monitoring provided by the alerts is negated by the vast number of alerts and provision of minimally important alerts in a manner that concealed more important alerts.

The invention relates to an intelligent behavior analysis and anomaly detection system for Internet of Things security, which is applied to the technical field of Internet of Things security, and comprises a data acquisition module, a data preprocessing module, a behavior modeling module and an anomaly detection module, the data preprocessing module cleans the data, the behavior modeling module generates a vector sequence of equipment behaviors through feature embedding and position coding, and the anomaly detection module analyzes time sequence association of the equipment behaviors by utilizing a self-attention mechanism and a multi-head attention mechanism and judges whether the equipment has abnormal behaviors or not. The cooperative defense module realizes cross-device cooperative defense through an edge detection unit and a cloud analysis unit, and the threat intelligence sharing module realizes sharing and updating of threat intelligence through a local intelligence database and an external intelligence interface. And the response module carries out automatic defense and notifies a system administrator through the automatic defense unit and the alarm unit when an abnormity is detected.

The invention discloses a database security secrecy system based on storage encryption, and relates to the technical field of information security. The database encryption platform is in communication connection with a key management module, an encryption and decryption management module, a performance monitoring module, a load evaluation module, a distributed storage optimization module, an early warning analysis module and an audit log module. According to the system, the early warning analysis module is combined with burden evaluation and security vulnerability detection of encryption and decryption performance, the abnormal degree of encryption and decryption processes is comprehensively analyzed, the early warning level is set, potential abnormal conditions are analyzed, and early warning information is sent out, so that a system administrator can respond in time, and the system safety is improved. A preposed risk management strategy enables a system administrator to take corresponding countermeasures before the risk actually occurs, thereby effectively reducing the influence of security threats, and meanwhile, according to different early warning levels, the countermeasures can be flexibly adjusted, and reasonable allocation of resources is ensured.

A system manager is implemented on one or more computing devices operating according to special-purpose instructions to detect anomalies and iteratively collect feedback for model re-evaluation. The system manager trains a machine learning model to detect anomalies and determines an accuracy score of the trained model at detecting anomalies in a set of data items. The system manager also determines a contiguous anomaly score value region that includes a threshold portion of incorrectly labeled outputs. The trained model is used to make predictions on production data, and the system manager determines an accuracy of the predictions by selecting a subset of the production data within the contiguous anomaly score value region, clustering the subset into clusters, and selectively sampling data items from the clusters. The accuracy of the predictions on the production data is combined with the accuracy score of the trained model to determine an updated accuracy score. The system manager determines whether to retrain the model based on the updated accuracy score.

The invention particularly relates to a method for realizing data watermark processing based on NiFi. According to the method for realizing data watermark processing based on NiFi, a data source connector is configured in a NiFi server, and a to-be-processed data stream is received in real time; a watermark embedding strategy is formulated, a watermark embedding algorithm is selected and optimized, watermark information is embedded into a data stream, and the data stream is transmitted to a target system or a storage medium by adopting an encryption means; extracting watermark information from the data stream with the watermark, verifying the extracted watermark information, and generating a verification result report; and a watermark verification result is fed back to a system administrator or a related user, and a watermark embedding and extracting report is generated. According to the method for realizing data watermark processing based on NiFi, the efficiency and the flexibility of data watermark processing are improved, the security and the integrity of the data are guaranteed, and powerful support is provided for secure transmission and copyright protection of the data and application of a data stream processing technology in more fields.

A method for reducing the risk of unexpected or unintended actions during a Remote Desktop Protocol (RDP) or SSH (Secure Shell) session by automatically detecting anomalies using vaulted credentials. The method includes initiating a RDP / SSH session on a server and taking screenshots of the session. The screenshots are sent to a system that uses a computer vision algorithm to transcribe the screen information into a text-based transcription of the session. The text-based transcription of the session recording is then provided to a pre-trained LLM which is prompted to look for anomalies using in-context learning. The detected anomalies are presented to a system administrator or sent as alerts to the system administrator.

Computational / communication system security tools are provided. Such tools report at least one multi-dimensional (or multi-component) data-object (based on the monitored events) to an administrator of the system. The multiple components of the data object provide multiple risk indicators (e.g., risk scores) along various dimensions of security for such systems. Thus, tools provide multi-dimensional monitoring and reporting of risks and security threats to computational / communication systems. The tools may also provide at least one risk mitigation action (e.g., quarantining and / or prohibiting particular risky entities, entity groups, and / or entity activities) based on the enhanced monitoring and detection methods presented herein.

The invention discloses an application performance monitoring method and system of a linux operating system, and the method comprises the following steps: continuously monitoring a performance index of a target application, tracking a key performance index of a system in a full-link manner, and monitoring a full life cycle related to business data; if the performance index of the target application is abnormal, triggering an alarm, recording an abnormal total system index, and recording an alarm log; intelligent analysis and pre-judgment are carried out on full-amount performance index data, prediction analysis is carried out on performance data through a machine learning algorithm, and possible performance problems are found in advance; and intelligent automatic tuning is realized in combination with expert experience. According to the method, the application performance indexes and the system indexes are monitored in real time, the abnormal results of the application performance indexes and the system indexes are integrated to obtain final performance index abnormal information and record the performance index abnormal information, the problem checking and solving process of a system administrator is greatly simplified, and meanwhile automation and intelligentization of operation and maintenance work are further promoted through intelligent analysis and intelligent adjustment and optimization functions.

An iterative publication method and system that connects data-based projects with publication is provided. An administrator logs into a computer system and creates a publication, specifying collaborators, contributors, data sources, analyses, visualizations, and more. Once a project is activated, the system generates written or pictorial elements of the publication(s). The publication has several relational and compound relational elements embedded within it's written or pictorial elements e.g. text, graphs, values, charts, and other similar data. The iterative publication system and method identifies the relational and compound relational elements, and updates these elements within the publication, as and when new data, or observations, or written or pictorial elements become available, thus providing a continually updating publication.

A system supports creation and use of cryptographic twins, which are cryptographically unique and private digital representations of entities. Twins can cryptographically encrypt and link an unlimited amount of data on behalf of their corresponding entities. The system can give entities cryptographic ownership and exclusive control over their own twins to preclude data access and tampering, even by system administrators. The system can be configured to recursively enable twins to cryptographically create, own and control other twins, to cryptographically transact with other twins, and to cryptographically transfer ownership and control of twins to other twins. As a result, the system can be configured to cryptographically chain twins to mirror complex ownership, control and transactional relationships that may exist between entities that the twins can represent in the real world.

The invention discloses an electric power carbon emission metering system based on an electric energy meter and a method thereof, and relates to the technical field of carbon emission metering. The electric power carbon emission metering system comprises a data acquisition and communication unit, a data processing and storage unit, a carbon emission factor management unit, a carbon emission calculation unit, a real-time monitoring and early warning unit and a report generation unit, and the output end of the data acquisition and communication unit is connected with the input end of the data processing and storage unit. The output end of the data processing and storage unit is connected with the input end of the carbon emission factor management unit, the output end of the carbon emission factor management unit is connected with the input end of the carbon emission calculation unit, and an early warning threshold value can be adjusted through an early warning rule setting module; a user or a system administrator is allowed to flexibly adjust the early warning threshold value of carbon emission according to actual needs.

A system, method, and computer-readable media for establishing a framework for managing application permissions in a group-based communication system. Upon receipt, from an application in a group-based communication system, of an attempt to access a target internet domain, an application manifest associated with the application is accessed. The manifest includes a list of approved internet domains previously approved by an administrator of the group-based communication system which the application may access. Following access of the manifest, it is determined whether the target internet domain is included in the list of approved internet domains. If the target internet domain is included in the list of approved internet domains, the application is allowed to access the target internet domain. If the target internet domain is not included in the list of one or more approved internet domains, access to the domain by the application is denied.

A network connected electronic lock system. The network connected electronic lock system includes a network connected electronic lock system management terminer (10), a network connected electronic lock system server (30), and a group of network interface module (50), a group of entrypads (60), and a group of lockbodies (70) are connected to the network (20) connected electronic lock system server (30) over a network (20). The network (20) connected electronic lock system is managed by a system manager over a network (20) connected electronic lock system management terminer (10) over the network (20) for one or more organizations. Each organization includes one or more branch offices (40). One or more network interface modules (50), one or more module (50), and one or more lockbodies (70) are installed in each branch office (40). Each entrypad (60) connects to the network (20) through the network interface module (50) and controls upto a predetermined number of lockbodies (70).

An illustrative data storage management system protects data in a replicated multi-node system (“cluster”). The illustrative system creates a new administrative entity (“pseudo-client”) that represents the cluster within the system. The system intelligently performs as an adaptive “set it and forget it” system. Preferences for the pseudo-client, including alternate rules that cover various contingencies in the cluster, need not be reset as the cluster undergoes node failures and / or role changes over time. Rather, the disclosed system adapts, on each successive secondary copy job, to the current configuration of the cluster without requiring a system administrator to provide further input or analysis. This approach ensures that jobs can begin promptly as scheduled or on demand. Component selection is based at least in part on geography / zone and / or network topology considerations, which improves the likelihood of job completion and success, and RPO / RTO service levels are more likely to be met.

The invention relates to a self-evolvable waveform system, method, equipment and medium, all attribute characteristics in radar signal analysis tasks are effectively covered by designing attribute types into seven types of numbers, characters, labels, files, enumeration, time and dimensions, and after the development task of basic information of the attribute characteristics is completed, the development task of the basic information of the attribute characteristics is completed. According to the method, the waveform system based on the real data of the radar signal analysis task can be rapidly established in the modes of entity construction, attribute binding and the like so as to further mine application requirements, and after the application requirements are determined, development and deployment of a final system can be rapidly completed based on the waveform system. Meanwhile, after the waveform system capable of self-evolution is delivered to a user for use, expansion and upgrading of system software functions can be completed only through a system administrator without intervention of professional software research and development personnel, and rapid self-evolution of the waveform system is achieved.

Ansible IntelScan is a groundbreaking software tool, characterized by innovative ideas and streamlined code processes. It leverages Ansible to aid system administrators and system engineers in executing their daily tasks more efficiently and effectively. The software eliminates the need for Ansible Modules or Roles, leading to significant time savings and cost reductions for companies. With its modular, user-friendly design, Ansible IntelScan is primed for routine tasks and report creation, serving as an asset for management decision-making. Its ease of use enables even junior administrators with minimal shell scripting knowledge to operate the software, thereby enhancing overall work productivity and cost-efficiency. Ansible IntelScan is compatible with large-scale Linux server environments, supporting simultaneous operations on over 1000 physical and virtual servers. This innovative tool has been rigorously tested and validated on popular Linux distributions such as Red Hat, CentOS, Ubuntu, and Debian in DEV, QA, and Production environments.Ansible IntelScan streamlines numerous critical operations including Linux system inventory reporting, cloud configuration, identification of unused cloud volumes, creation of multiple users, and customized security vulnerability scanning. The tool's efficacy has been proven in a variety of applications, such as system inventory management, labor-hour reduction in security company operations, cost savings through the identification of unused cloud resources, timesaving in user creation for US DOD and government projects, and the creation of customized vulnerability scan tools for enhanced security compliance.With the incorporation of advanced features like playbook execution and report generation, Ansible IntelScan emerges as a dynamic and resourceful toolset for system administrators at all levels of experience.

The systems and methods disclose an automated effective template generation and recommendation for selection. A semantic similarity of a plurality of messages may be identified that at least meets a similarity threshold, each of the plurality of messages reported by a plurality of users as a potentially malicious message. The plurality of messages may be indexed under a common template identifier. One or more messages of the plurality of messages indexed under the common template identifier may be determined to have a report-to-reach ratio less than a report-to-reach threshold. Responsive to the determination, the one or more messages may be identified to be used for generating one or more simulated phishing templates. A recommendation of the one or more templates may be provided to a system administrator and / or a security awareness and simulation training platform to create and deliver simulated phishing messages using the templates.

The invention discloses an intelligent isolation and asynchronous cleaning HDFS recycle bin design method and system, and the method comprises the steps: creating an independent recycle bin directory for each user; one metadata file is maintained under each recycle bin directory; setting access permissions of a specific user and a system administrator for each recycle bin directory; metadata in a recycle bin of files is stored in a RocksDB, and two tables are designed in the RocksDB: the table 1 is used for clearing out expired files, and the table 2 is used for recovering and displaying the files; when the file is deleted, determining a recycle bin ID of a user according to a path before the file is deleted, and inserting recycle bin metadata of the file into the RocksDB; the specified file is found and recovered by querying metadata in the table 2, and the RocksDB is updated; and cleaning the expired file regularly or as required by utilizing the self-defined expiration time in the table 1, and updating the RocksDB. According to the method and the system, the problems of performance bottleneck and management complexity of the Hadoop recycle bin in a high-concurrency and large-data-volume scene are solved.

The invention provides a supplier management system, method and device and a medium, and belongs to the technical field of enterprise supply chain digital management, and the system comprises a multi-role collaborative management module which carries out the user role authority control management of suppliers, service providers, internal inspection departments, internal purchase operation departments and system administrators; the contract and order management module is used for receiving signed electronic contracts and generating hardware and software orders; the order acceptance module is used for receiving quality inspection results of hardware and software by an internal inspection department and outputting acceptance data; the dynamic evaluation module calculates scores of suppliers and service providers according to the acceptance data and historical acceptance data; the automatic payment module is used for paying the payment amount according to the scoring results of the suppliers and the service providers and the content of the electronic contract and updating the state of the contract; and the risk control list module is used for freezing the suppliers and the service providers which exceed the set times of low-score risk early warning. The supplier management process is optimized, the efficiency is improved, and the risk is reduced.

According to the music practical training system and device based on the virtual reality technology, a virtual reality function is introduced, and practical training data such as playing actions, playing sound effects and tones in the music practical training process are collected; in combination with a virtual reality practical training module of a music practical training system, separation of data acquisition and data configuration of a virtual reality display interface is realized based on display requirements and data structure configuration related to virtual reality specific functions, and an autonomous practical training effect feedback mechanism is provided for a system administrator. And a system manager determines how to feed back and display related practical training data and practical training effects in the music practical training process, and guides music practical training according to virtual reality display data.

Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users / admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.

A public toilet alarm and response system comprises a cleaning administrator mobile terminal, a system administrator mobile terminal, an alarm terminal, an alarm switch and a toilet cubicle detection module. Each toilet cubicle of each public toilet is internally provided with an alarm switch which is used for sending an alarm signal after being passively triggered or actively triggered, and a toilet cubicle detection module which is used for enabling the corresponding alarm switch to be actively triggered when the toilet cubicle is used overtime; the non-toilet-cubicle public area in each public toilet is provided with an alarm end which displays the corresponding toilet cubicle after receiving the alarm signal and uploads the alarm information to the cloud server; the cloud server receives alarm information uploaded by the alarm end, forwards the alarm information to the system administrator mobile end and the cleaning administrator mobile end managing the toilet cubicle, and stores alarm records. The system is high in response real-time performance, low in power consumption, high in reliability and convenient for system optimization based on big data, and the manual inspection burden of a cleaning administrator is reduced.

The invention provides a federal learning method for enhancing robustness and protecting medical privacy, and solves the technical problems that heterogeneous data in an intelligent medical scene is difficult to aggregate and malicious participants are poisoned and attacked. According to the technical scheme, the method comprises the steps that S10, a system administrator SM and a scientific research institution RI generate public parameters and distribute a key set; s20, the hospital uses the local data set to train model parameters, normalizes and encrypts the model, and uploads the encrypted model to a server of the RI; s30, the SM and the RI cooperatively carry out normalization judgment, and the RI evaluates a gradient ciphertext by using cosine similarity; s40, the RI uses a logistic regression function to adjust the aggregation weight of the gradient ciphertext, and then the gradient ciphertext is aggregated; and S50, the RI and the hospitals participating in training jointly update the local model. According to the method, a fully homomorphic encryption algorithm is used for protecting privacy data of medical patients, cosine similarity is used for evaluating gradient ciphertexts, and a new aggregation mechanism ensures that a training model has high accuracy.

The application discloses a kind of digital engineering cost index determination method, system, equipment and storage medium, wherein, method includes: receiving enterprise index subject and enterprise standard list uploaded by system administrator;Receive the configuration input of system administrator;According to the configuration input, the association of enterprise index subject and enterprise standard list is configured, and the calculation rule of each index in enterprise index subject;Obtain the data input by user for enterprise standard list;From the data of enterprise standard list associated with enterprise index subject, obtain the target data required for calculating the index in enterprise index subject;According to calculation rule, target data is processed, and the information for determining the index value in enterprise index subject is obtained.The application can upload enterprise index subject and enterprise standard list according to the needs of enterprise, and when calculating the index in enterprise index subject, the required data for calculation can be automatically obtained from the associated enterprise standard list.

The invention discloses a method and system for improving automatic horizontal and vertical elastic capacity expansion and contraction of a middleware platform. The method comprises the following steps that S1, installation of middleware is constructed, and a Helm Chart product package is deployed; s2, visual deployment is carried out through a KubeSphere platform; s3, deploying a horizontal and vertical capacity expansion and contraction trigger module developed by a Golang language to a cluster; and S4, setting a cyclic feedback mechanism, continuously monitoring a resource state and automatically adjusting the resource state. The invention provides an efficient and extensible solution, and provides a simplified and efficient middleware operation and maintenance automatic management technical method for developers and system administrators.

The real-time ransom and security breach detection and prevention system empowers users and system administrators by providing real-time threat detection and prevention by detecting any phishing links, malicious executables and objects, and manipulation of authentication tokens that could potentially escalate a threat into ransom attacks, security breaches or other cyber attacks, and take immediate action by blocking and reporting the potential security breach before escalating into a real attack. The real-time ransom and security breach detection and prevention system generates a first hash of the link, executable, object, or authentication token. Utilizing this generated first hash, the real-time ransom and security breach detection and prevention system calculates a second hash upon user interaction or at runtime and compares the two unique hashes to determine if the link, executable, object, or authentication token is corrupt and terminates the gateway to prevent the cyber-threat from infecting the system.