679 results about "Security information" patented technology

A federated distributed computational system enables secure collaboration across multiple institutions for biological data analysis. The system consists of interconnected computational nodes managed by a centralized or decentralized federation manager, depending on the deployment model. Each node contains specialized components that work together to process biological data while preserving privacy. These components include a local computational engine that handles data processing, a privacy preservation module that protects sensitive information, a knowledge integration component that manages biological data relationships by connecting various data sources, and a communication interface that enables secure information exchange between nodes. The federation manager coordinates all computational activities across the network while ensuring data privacy is maintained throughout the process. This architecture allows research institutions to collaborate on complex biological analysis tasks without compromising their sensitive data, enabling breakthrough discoveries through shared computational resources and expertise while maintaining the security, compliance, and confidentiality required in biological research.

The invention relates to the technical field of network and information security, and discloses a multi-source security information collaborative analysis method and system fused with an AI intelligent agent, and the method comprises the steps: collecting security related data; cleaning and normalizing the collected data, and extracting target security features from the preprocessed data; constructing a plurality of AI agents for different data sources, and generating a preliminary threat judgment result through semantic understanding, behavior pattern recognition and association rule mining based on target security features; performing time sequence fusion on the preliminary threat judgment result, constructing a dynamic security situation model, capturing a threat evolution trend, and dynamically determining a risk level and a priority processing sequence of an event in combination with threat intelligence; according to the risk level and historical response experience, the AI intelligent agent generates an automatic response suggestion and pushes the automatic response suggestion to operation and maintenance personnel; according to the invention, the threat identification capability is improved.

The invention relates to the technical field of network operation and maintenance, in particular to an automatic operation and maintenance method and system based on artificial intelligence, and the method comprises the steps: collecting detailed log information containing a security event in real time through a security information and event management system configured at a target endpoint; performing cleaning, labeling and structured processing on the log data by utilizing a proxy artificial intelligence system to generate standardized metadata, and performing MITRE ATTamp with the standardized metadata; mapping the CK knowledge base, identifying technical features and behavior patterns of attacks, comparing enriched log data with an external threat intelligence source, analyzing TTP of a known attack group, generating a threat intelligence association report, generating a targeted response plan by using a large language model, generating an executable command sequence according to the response plan, and generating a threat intelligence association report; the proxy executor is connected with the server through a WebSocket protocol, executes a command in a POSIX shell environment, captures and returns an execution result, verifies the execution result, carries out necessary command optimization, records an optimized response to a vector database, and automatically matches a historical event and triggers a predefined response process through a vector retrieval mechanism. And continuous threat monitoring and adaptive response are realized. According to the method, the problem that a closed loop aiming at a terminal executor, data enrichment and historical event recall cannot be formed by security operation and maintenance in the prior art can be solved.

The invention discloses a construction site safety monitoring method and system based on a large model and RAG, and the method comprises the steps: carrying out the intelligent analysis of real-time video data of a construction region based on a visual large model, and recognizing the behavior safety, violation operation, dangerous facilities and environment risks of construction personnel; adding a time label to the analyzed security event text to form a construction site security event log; reasoning and analyzing the security event log, determining whether security early warning is generated or not, and pushing early warning information; carrying out on-site intelligent voice broadcasting according to the early warning information; through a multi-RAG architecture, a construction site safety log database, a public construction safety management database and an enterprise internal safety management database are constructed, and construction safety information is stored by using a vector database and a graph database. By adopting the technical scheme of the invention, the problems of insufficient real-time monitoring capability, limited intelligent analysis capability and lack of effective knowledge base support in the existing construction site safety supervision are solved.

The invention relates to the technical field of network security, and discloses a network traffic anomaly detection method and system based on a knowledge graph, and the network traffic anomaly detection method comprises the following steps: protocol perception metadata feature extraction: extracting metadata features which do not involve content privacy from encrypted network traffic through a deep packet inspection technology, comprising flow statistical characteristics, time sequence characteristics and connection relation characteristics; multi-level knowledge graph construction: based on the extracted metadata features, according to a network architecture, respectively constructing corresponding knowledge graphs on a device layer, a gateway layer and a cloud layer, and respectively representing device behaviors, network activities and global security information; the method does not depend on flow decryption operation, effective recognition of abnormal behaviors in the encrypted flow is achieved only by analyzing the metadata features of the network flow, and therefore the detection accuracy is improved.

The invention belongs to the technical field of information security, and particularly relates to a super-threshold data set intersection method and system for security information processing. The method comprises the following steps: S1, carrying out casual key value pair storage OKVS encoding and decoding between each participant and other participants; s2, each participant constructs a hash table according to a decoding result and elements of the participant; and S3, sending the constructed hash table to a specified party, summarizing information in the hash tables of all participants by the specified party, and finally obtaining a super-threshold intersection result by using a secret sharing scheme. The method has the characteristics that the hardware and operation and maintenance cost can be reduced, the data security is enhanced, and the calculation efficiency is improved, so that the industrial control requirement of short-time response is met.

An electronic device is provided. The electronic device includes a communication module, a memory, and a server processor operably connected to the communication module and the memory. The server processor acquires, from the first electronic device, a first message encrypted based on first security information about the second electronic device, so as to transmit the first message to the second electronic device, acquires, from the second electronic device, a decryption failure signal for the first message so as to transmit the decryption failure signal to the first electronic device, acquires, from the second electronic device, second security information about the second electronic device so as to transmit same to the first electronic device, receives, from the first electronic device, a second message encrypted based on the second security information, and can transmit the received second message to the second electronic device.

Disclosed in the present invention is a smart port management system based on a blockchain. The system comprises: a cargo information collection module, which is used for collecting cargo information; an information uploading module, which is used for performing on-chain processing on the collected cargo information and uploading the cargo information to a blockchain; a cargo conveyance collection module, which is used for collecting information related to cargo conveyance in a port by unmanned conveying devices in the port; a vehicle information collection module, which is used for collecting information related to vehicles entering the port; a personnel information collection module, which is used for collecting personnel information in the port; a port protection collection module, which is used for collecting information related to protection devices at port terminals; and a security history collection module, which is used for collecting historical security information of the port. The present invention enables more comprehensive and smart port management.

Processors, systems, methods, and computer program products to detect unauthorized modifications to security information in a security device. In at least one embodiment, a processor comprises one or more circuits that use information stored in one or more storage locations of one or more security devices to detect whether the security devices have been rebooted.

One example method includes receiving, by a confidential container service from a tenant, a request to provision a tenant node, provisioning the tenant node using a multi-tenant trusted execution environment (TEE) attested resource provisioning process, receiving, from the tenant, tenant-specific security information concerning the tenant node, storing the tenant-specific security information in a tenant-specific catalog, implementing security procedures, specified in the tenant-specific security information, in the tenant node, and upon successful authentication of the tenant, using the security procedures, enabling the tenant to access the tenant specific confidential resources from the tenant node(s).

The invention provides a security information reading method and device. The security information reading method comprises the steps of obtaining a current life cycle corresponding to a target chip under the condition that a reading request of reading security information of the target chip is received; a target reading position is selected from a first storage unit and a second storage unit according to the current life cycle, the first storage unit is used for storing safety information injected into a target chip after the chip leaves a factory, and the second storage unit is used for storing safety information injected into the target chip during chip design and production; and reading the target security information stored in the target reading position. By means of the safety information reading method, the probability of potential safety hazards existing in a factory chip is reduced.

Systems and methods for generating predicted end-to-end cyber-security attack characteristics via bifurcated machine learning-based processing of multi-modal data are disclosed. The system accesses multi-modal data indicating a set of security information related to a computing system. The system then generates a set of extracted characteristics indicating a cyber-security attack on the computing system, via a supervised machine learning model, using the multi-modal data. Using this information, the system generates a revised set of extracted characteristics indicating the cyber-security attack, via an unsupervised machine learning model, using the extracted set of characteristics indicating the cyber-security attack, where the revised set of characteristics includes at least one new characteristic that was not included in the extracted set of characteristics indicating the cyber-security attack on the computing system. The system then generates for display a graphical representation of the revised set of extracted characteristics.

The invention discloses a smart park security system based on a GIS technology, and belongs to the technical field of security protection. Comprising a GIS basic service module, a security element plotting module, a basic element visualization module, a multi-source heterogeneous security information integration module, a data storage and management module, a depth feature extraction module, a model training and real-time reasoning module and a control response and verification module. And the GIS basic service module is used for providing a unified space reference and geographic information service and supporting coordinate conversion, space analysis and map rendering. Based on the unified space reference capability of the GIS basic service module and in combination with the GPS RTK positioning and Beidou dual-mode positioning of the security element plotting module, precise space association of the park security equipment is realized, the plotting position is precise, the real-time operation state of the equipment can be deeply bound with GIS coordinates, and a manager can intuitively master the dynamic state of the equipment through a map, so that the management efficiency is improved. The problems of fuzzy plotting and state disjunction of a traditional system are solved.

The invention relates to the technical field of railway safety informatization, in particular to a railway external environment hidden danger intelligent extraction data storage and visualization system. The system is composed of a hidden danger intelligent extraction model integration module, a multi-source data storage module, a multi-source data visualization and hidden danger standing book module and a risk assessment and space analysis module. The front end is constructed based on a Vue framework, the rear end is constructed based on a Flask framework, and data interaction is performed through a RESTful API. According to the system, intelligent hidden danger extraction and dynamic display are realized through fusion of a deep learning algorithm and multi-source data; efficient image processing and distributed storage are adopted, so that the false detection and omission ratio is reduced; the modular design and the micro-service architecture optimize the resource configuration and reduce the operation cost; the visual front-end interface and the interactive design improve the user experience and simplify the operation process; intelligent extraction, efficient storage, visual display and accurate analysis of railway external environment hidden danger data are realized.

The invention discloses a micro-service secure communication method and system, electronic equipment and a storage medium, which are used for realizing communication between a request micro-service and a target micro-service, and the micro-service secure communication method comprises the following steps: generating security information based on the micro-service, the security information comprising identity information and authority information; requesting the micro service to initiate a calling request; generating encrypted data based on the calling request; generating an operation certificate based on the calling request, wherein the operation certificate comprises user identity information and operation content; and the target micro-service obtains the encrypted data and calls the operation basis and the security information to carry out security verification, and when the verification is passed, response data is generated and sent to the request micro-service. According to the invention, a comprehensive security mechanism of identity verification, authority control, data encryption and integrity protection is realized, so that the security risk is effectively reduced, and the security and reliability of communication between micro-services of different domains are ensured.

A security feed normalizer aggregates and normalizes threat intelligence data across security feeds and extracts threat descriptors of cybersecurity threats from the aggregated / normalized data. A first large language model (LLM) determines whether each threat descriptor is informative, i.e., comprises sufficient information for reproducing / generating network traffic of the corresponding cybersecurity threat. For informative threat descriptors, a second LLM generates network traffic for the corresponding cybersecurity threats. The generated network traffic is used for subsequent remediation of corresponding threats.

The invention discloses an event association analysis and early warning system for a security information management platform, and the system comprises an event identifier generation module, an event feature association module, an abnormal event discrimination module, an early warning response execution module, and an early warning triggering module, a data storage module and a behavior verification module. The event identifier generation module determines the association importance in combination with the event emergency level, the type label and the occurrence frequency, and generates a unique identifier; the event feature association module integrates initial, stage and continued feature acquisition values, and compares the values with a reference to form a result; the abnormal event judgment module determines an abnormal monitoring quantity by analyzing a state and the like, and identifies abnormal associated information; and the early warning response execution module optimizes a response path based on a multi-dimensional model in combination with the association importance and historical data. The system improves event identification accuracy, feature association comprehensiveness and the like, and is suitable for security and protection information management.

The invention discloses a comprehensive monitoring platform for an auxiliary system of an intelligent substation, and the platform comprises a sensing layer which is provided with diversified sensors and is used for collecting the operation state, environmental parameters, security and protection information and fire-fighting information of equipment in the substation in real time, and the sensors have the self-diagnosis and self-calibration functions; the edge computing layer is composed of a plurality of edge computing gateways; the cloud platform is used for carrying out deep fusion, storage, analysis and intelligent decision making on the data uploaded by the edge computing node; and the application layer is used for providing an interactive interface and a functional module for a user, and the user can log in the technology through various terminal devices. Through a multi-level architecture and an intelligent analysis technology, comprehensive perception, intelligent analysis and automatic control of equipment states are realized, faults are predicted in advance, downtime is reduced, and reliability and stability of a power system are improved. The response time is shortened by an intelligent linkage strategy and an edge computing local decision-making mechanism, sudden safety events and equipment faults can be quickly handled, and accident loss is reduced.

This invention discloses an automatic robot instruction inspection method and apparatus based on the PDPS platform. The method involves acquiring offline program data of the robot and the corresponding design rules, configuring a program inspection tool according to the design rules, inputting the program data into the inspection tool, and storing safety information from the first and second instructions into corresponding variables. The information in each variable is compared or judged to obtain a first judgment result. Chinese characters and punctuation marks in the program data are judged to obtain a second judgment result. Based on the motion parameters in the program data, the margin value of each joint when the robot performs each action is calculated, and collision risk is judged based on the margin value to obtain a third judgment result. Finally, the robot's compliance with safety rules is judged based on the motion radius to obtain a fourth judgment result. This method improves the accuracy of offline program inspection.

The invention discloses an industrial asset association analysis method and system based on a large model, and relates to the technical field of industrial asset association analysis, and the method comprises the steps: obtaining information which comprises business process data and security data; preprocessing the information to obtain preprocessed data; the preprocessed data are input into a trained big language model, the trained big language model analyzes the business process data and carries out scenario processing on the security data, and analyzed business process information and scenario security information are output; and inputting the analyzed business process information and the situational security information into a trained big language model, and identifying the association between the analyzed business process information and the situational security information by the big language model to obtain an association result. According to the invention, the potential influence of security vulnerabilities, alarms or events on specific business functions and overall operation continuity can be evaluated.

The invention relates to the field of social security management data processing, and discloses a social security information intelligent analysis system based on dynamic closed-loop regulation, and the system comprises an analysis prediction unit which calculates a risk score based on a feature weight; the subthreshold residual cutoff unit captures weak score data lower than a trigger threshold value; the space-time entropy aggregation unit calculates the Shannon entropy of the weak data; the agility bias unit reduces the trigger threshold according to the low-entropy aggregation state; the self-adaptive damping correction unit utilizes a predicted and feedback difference vector to reversely correct a feature weight, the environmental background pressure is sensed by calculating a space-time entropy value of discarded residual data, a trigger threshold value is dynamically biased according to the environmental background pressure, a damping mechanism correction model is introduced into a feedback closed loop, and a damping mechanism correction model is introduced into the feedback closed loop. The problem of weak risk report omission caused by a fixed threshold value is solved, and self-adaptive dynamic balance of system sensitivity and false alarm rate is realized.

The invention discloses a collaborative supervision method and system for a construction project, and relates to the technical field of construction project supervision, and the method comprises the steps: obtaining various types of basic information of the construction project; and based on the real-time change characteristics of various types of information in the basic information, determining differential collaborative supervision period information. According to the collaborative supervision method and system for coping with the construction project, the collection points covering the whole range of the construction area are used; four types of core information including engineering design data such as a structure change list, a construction progress record such as process connection time, a material quality certificate such as a steel bar mechanics detection report and an on-site safety inspection result such as a scaffold acceptance record are synchronously obtained, and accurate classification is carried out according to features; the collaborative acquisition of the multi-source information thoroughly changes the one-sidedness in the traditional supervision; in the residential building construction process, a supervisor can rapidly position the root cause of the problem, namely insufficient personnel qualification instead of materials, by integrating the material information and the safety information, and misjudgment caused by single information is avoided.

Disclosed in the present invention is a traffic all-domain safety early warning system based on real-time safety information fusion technology, comprising a traffic all-domain big data cloud center, an onboard intelligent terminal OBU, an intelligent terminal having a client APP installed thereon, and a roadside unit RSU; the onboard intelligent terminal OBU is used for acquiring vehicle self-collected information serving as a first-layer information source; the roadside unit RSU is used for acquiring RSU information serving as a second-layer information source; the intelligent terminal having a client APP installed thereon is used for acquiring all-domain traffic information serving as a third-layer information source; and the traffic all-domain big data cloud center corrects the accuracy of dynamic traffic data comprising the vehicle self-collected information, an RSU information source and the all-domain traffic information, and fuses the corrected data into a unified traffic electronic map. The present invention ensures that all types of individuals entering the public traffic space can be detected in advance, thereby improving the information transparency and operation efficiency of the traffic system, and travel safety.

A method of security information visualization processing, an electronic device and a storage medium are provided. The method includes: in response to a security overview display instruction, displaying a security overview dashboard of a user group; displaying, in the security overview dashboard, anomaly aggregation information and security measure aggregation information; and aggregately displaying, in a display region corresponding to a security scenario, information of a plurality of anomaly categories associated with the security scenario.

The invention discloses a data application security protection method and device adaptive to a novel power system, and relates to the technical field of novel power systems. According to the main technical scheme, firstly, a feature recognition model is used for conducting preliminary recognition, preliminary classification, redundancy removal and catalogue classification establishment on a large amount of interface communication between micro-services, which is equivalent to preprocessing of a large amount of interface communication data, and then on the basis, the content of the communication data is calculated. Especially, according to the label classification and service data corresponding to the interface communication, the security information of the interface communication is analyzed so as to provide a solution of security protection on the interface communication level.

A method and apparatus for transfer of security information from a Centralized Unit (CU) to a Distributed Unit (DU) is provided. A serving DU receives security information related to a candidate cell from a serving CU. The security information is for security update upon cell switch. The serving UD transmits a cell switch command for the cell switch from the serving cell to the candidate cell, to the wireless device. The cell switch command includes the security information related to the candidate cell based on the candidate cell belonging to a CU different from the serving CU.

The aviation safety oversight software will be utilized by the civil aviation authority to monitor the safety performance of aviation service providers. This software will first classify the air operating companies and then create an electronic file to update the regulatory processes of the civil aviation authority according to the applicable air operating companies and the aviation safety performance indicators of the country. The software aims to streamline the implementation of the regulatory processes of the Civil Aviation Authority. It will use statistical analysis to convert safety data into safety information for better analysis and decision-making.

The invention provides an address standardization and dynamic management method, which belongs to the technical field of information processing, and comprises the following steps: inputting collected address information into a hierarchical entry framework to perform hierarchical division on the address information; converting the non-structural data of each hierarchy into initial structural data, splitting the initial structural data according to the expression combination of the corresponding divided hierarchy, respectively performing authenticity judgment on the initial structural data and the corresponding expression standard under the expression combination, and constructing an authenticity vector and an authenticity attribute vector; the existence reliability of the same corresponding element in the two personality vectors is analyzed, and unreliable elements are screened; establishing an association relationship between the unreliable element and an unsuccessfully divided part in the first storage block, calling a historical standard hierarchical description, and correcting the description to obtain a standardized address; and determining historical security information of each transmission interface for transmitting the standardized address and a receiving interface of the big data platform in a specified time period, and establishing a security protection mechanism. Standardized processing of address information and safe and reliable transmission of information are realized.

The application provides a communication method and device, relates to the field of communication, and can realize anti-packet attack while guaranteeing the continuity and real-time performance of services. The method comprises the following steps: a first network device receives a first packet from a terminal and sends a second packet to a second network device. The second packet is obtained by encapsulating security information in the first packet, and the security information is used for indicating that the second packet is a trusted packet determined by the first network device.