1284 results about "Security information" patented technology

Cybersecurity components configured to cooperate with LLMs including i) a cyber security appliance with a cyber threat detect engine to detect a cyber threat, ii) a proactive threat notification service, iii) a cyber threat autonomous response engine, iv) a cyberattack simulator, v) a cyber-attack restoration engine, and vi) an artificial intelligence-based cyber threat analyst module. The LLMs are configured to communicate and cooperate with the one or more cybersecurity components via one or more Application Program Interfaces (APIs) to receive cyber security information being produced by the one or more of the cybersecurity components and then to apply language generation functionality in order to assist a human in an understanding of the cyber security information being produced by the cybersecurity components, and then also to provide recommendations to prioritize breaches over other breaches in a native human friendly format for the human.

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.

An interactive cyber-security user-interface for cybersecurity components can receive a voice input from a user as well as ii) a text input as a user input. The interactive cyber-security user-interface works with a set of differently trained LLMs to carry out tasks on behalf of the user input. The interactive cyber-security user-interface cooperates with the set of differently trained LLMs, which are grouped together to operate as an orchestrated system to provide different tasks. The tasks can include a collection of supplementary information, a summarization of cyber security information, translating a query in the natural human speech format into the required search syntax, how to integrate with an API, acting as a first line of support to user inquiries, a suggested response to a cyber security issue, etc. The interactive cyber-security user-interface for the cybersecurity components acts as the user interface for one or more of the cybersecurity components.

Systems and methods for predictive analysis of potential attack patterns based on contextual security information are described. In one embodiment, a method includes generating a profile for an enterprise that indicates one or more software application stacks and a network architecture for the one or more software application stacks; determining one or more vulnerabilities of the one or more software application stacks and one or more vulnerabilities of the network architecture; providing the one or more vulnerabilities of the one or more software application stacks, the one or more vulnerabilities of the network architecture, and the profile as input to a machine learning model; generating an inference by the machine learning model that indicates one or more attack paths for an attacker in the one or more software application stacks and the network architecture; and transmitting the inference to a storage location or a security software application.

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 relates to the technical field of equipment access authentication, and discloses an equipment access authentication method and device, equipment and a storage medium. The method comprises the following steps: monitoring and collecting server equipment to obtain a first server feature vector; processing through a time domain multiple sparse Bayesian learning algorithm to obtain a server behavior reference model; calculating a second server feature vector collected in real time to obtain a server state abnormity score; triggering a multi-modal analysis program and carrying out deep evaluation to obtain a server abnormal behavior report; analyzing through a deep reinforcement learning algorithm to generate a server dynamic access control strategy; according to the method, a device access authentication system which is safer, more reliable and higher in adaptability is constructed by comprehensively and dynamically analyzing device behaviors and combining an intelligent algorithm and a cooperative defense mechanism so as to cope with various security challenges in the current network environment.

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 provides a construction site safety information supervision system based on the Internet of Things, and relates to the technical field of data processing, the risk assessment accuracy is remarkably improved and the data noise interference is inhibited through a deep reinforcement learning dynamic optimization grading early warning strategy and in combination with a multi-source data compression and federated learning framework; a risk coupling model is constructed based on a complex network theory, a conduction path and a linkage effect between regions are analyzed, a global early warning scheme is optimized, and the adaptability of the system to a complex construction environment is enhanced; the model is continuously optimized through a dynamic weight updating mechanism, high adaptability is kept under the environment change of a construction site, meanwhile, a resource dynamic allocation strategy is adopted, the problem of low high-concurrency processing efficiency is effectively solved, and the overall accident early warning accuracy is improved.

Methods and apparatus for dynamically selecting an action to be taken in an environment. A method comprises receiving, at a ML agent hosting the plurality of ML models, information about a state of the environment, wherein the information about the state of the environment comprises safety information, and analysing the safety information to determine a risk value for the state of the environment. The method further comprises selecting one of the plurality of ML models, wherein the selection is based on the determined risk value, and processing the information about the state of the environment using the selected ML model to generate a state prediction. The method also comprises generating one or more suggested actions to be performed on the environment using the state prediction.

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 discloses a transmission method and device, Internet of Things equipment and electronic equipment, and belongs to the technical field of communication, and the transmission method comprises the steps that target Internet of Things equipment receives a first downlink message sent by first equipment, and the first downlink message is used for indicating at least one piece of Internet of Things equipment to initiate a random access process; wherein the first downlink message comprises at least one of the following items: identification information of the at least one piece of Internet of Things equipment; a cause is paged; accessing process information; transmitting data information; the access resource configuration information of the target Internet of Things device; time control information; the retransmission resource configuration information of the target Internet of Things device; the security information is used for carrying out authentication on the target Internet of Things equipment and carrying out encryption or decryption on transmission data; and a first indication, wherein the first indication is used for indicating the backoff time of data retransmission of the target Internet of Things equipment.

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.

Various aspects of the present disclosure relate to an authentication server function (AUSF) that receives an authentication request from a security anchor function (SEAF), and transmits a data request for authentication data to unified data management (UDM). The AUSF can receive the authentication data from the UDM for primary authentication, and set an expiration time for security information associated with the primary authentication being successful. The AUSF can then transmit an authentication message of authentication information that includes the security information and the expiration time to an authentication and key management for applications (AKMA) anchor function (AAnF) that registers the expiration time. The AUSF can also initiate reauthentication based at least in part on expiry of the authentication information.

Disclosed are systems, apparatuses, methods, and computer-readable media for providing security postures for a service provided by a heterogenous system. A method for verifying trust by a service node includes receiving a request for a security information of the service node from a client device, wherein the request includes information identifying a service to receive from the service node, identifying a related node to communicate with the service node based on the service, after identifying the related node, requesting a security information of the related node, generating a composite security information from the security information of the service node and the security information of the related node, and sending the composite security information to the client device. The composite security information provides security claims for a service implemented by a heterogenous devices that have different trusted execution environments.

The invention relates to the field of satellite communication, and provides a satellite base station switching method and device and a computer readable storage medium, which can support SDT of terminal equipment in an RRC inactive state in NTN, effectively reduce the power consumption of the terminal equipment and improve the transmission efficiency. Under the condition that a source satellite currently serving a first cell needs to be switched to a target satellite, the source satellite sends first information (such as security information, context information and cell configuration information) related to the first cell to the target satellite, and after the target satellite receives the first information, related configuration is carried out in the target satellite. Therefore, as the context information of the terminal equipment in the RRC inactive state is stored and configured in the target satellite, in the process that the target satellite serves the first cell, the terminal equipment in the RRC inactive state can send the uplink small data, and the target satellite can quickly receive the uplink small data.

The invention discloses an industrial control intrusion detection method based on an ISAE auto-encoder and AFF feature fusion, and relates to the field of industrial control network security. The problem that a conventional intrusion detection algorithm is generally only based on a data set formed by original traffic data and manually extracted features, and due to the fact that traffic features cannot be deeply mined, obtained safety information is not comprehensive enough, and the effect of detecting partial attack traffic is poor is solved. The method comprises the steps of collecting original traffic data, obtaining corresponding artificial features according to the original traffic data, and constructing a training data set according to the artificial features; performing data preprocessing on the original flow data and the artificial features; constructing an intrusion detection model and training the intrusion detection model; and inputting the test set data into the trained intrusion detection model to obtain an intrusion detection result. The method is suitable for detecting and monitoring network intrusion, and the network intrusion risk is reduced.

The embodiment of the invention discloses a data security situation awareness platform construction method and device and electronic equipment. The method comprises the following steps: acquiring network communication data of a to-be-constructed subject, and extracting the network communication data to obtain information transmission data of the to-be-constructed subject; performing analysis according to the information transmission data of the to-be-constructed subject to obtain an information transmission topological structure model; analyzing the information transmission data of the to-be-constructed subject to obtain non-security information transmission data; constructing an abnormal information transmission detection model according to the non-security information transmission data, and performing detection to obtain real-time abnormal information transmission data; integrating the information transmission topological structure model to obtain abnormal node link data; analyzing according to the abnormal node link data and the information transmission data of the to-be-built subject to obtain a security information transmission link structure model; the invention discloses an information transmission security situation awareness platform. According to the invention, data security or network security events can be avoided, and a better network environment is provided.

This application discloses a security assessment method and apparatus, an electronic device, and a readable storage medium. The security assessment method is applied to an electronic device that supports a trusted execution environment TEE and a rich execution environment REE, where the method includes: in a case that a security information query request for querying a security status of the electronic device that is sent by a server is received by the REE side, obtaining REE security status information and sending the security information query request and the REE security status information to the TEE side; obtaining target security information from the TEE side and generating comprehensive security information based on the REE security status information and the target security information, where the target security information includes TEE security status information; and sending the comprehensive security information to the server.

The invention provides a flight communication system of a single Beidou module unmanned aerial vehicle and a flight control method thereof, relates to the field of unmanned aerial vehicle communication, and comprises a flight communication scheme and communication maintenance measures. By setting communication stability guarantee measures and a communication safety protection scheme, the operation stability and safety of the communication system can be effectively improved, normal operation of the unmanned aerial vehicle in the aspect of communication can be guaranteed, communication content can be effectively compressed and optimized by setting a communication optimization strategy, and the communication safety of the unmanned aerial vehicle is improved. Meanwhile, in cooperation with transmission scheduling optimization, key safety information, real-time control instruction response and the like of the unmanned aerial vehicle can be well arranged to be transmitted in a high-priority time period to ensure timely delivery, the communication transmission efficiency is ensured, and through the organic combination of a neural network algorithm and a PID control algorithm, the safety of the unmanned aerial vehicle is improved. The unmanned aerial vehicle can deal with various complex flight conditions more intelligently and accurately, and the efficiency and accuracy of route correction are effectively 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.

The disclosure relates to wireless communication systems and devices and methods thereof, and to lower layer triggered mobility, LTM. Apparatus and methods for supporting inter-CU based LTM are disclosed. Apparatus and methods for exchange of security information during inter-CU based LTM are disclosed.

The invention discloses an information security data processing system based on a block chain, and belongs to the technical field of information security processing. The method is used for solving the technical problem that in an existing scheme, the autonomous multi-dimensional supervision processing effect of storage of security information of different storage types of a block chain is poor. By monitoring, processing and analyzing multi-dimensional storage of security information of different storage types of the block chain before each storage, the storable state of the storage type corresponding to the to-be-stored security information is determined, and the storage request of the to-be-stored security information is dynamically managed in a self-adaptive manner. The autonomous supervision and processing effect of storage of security information of different storage types of the block chain is improved from a local dimension; all local security information storage processing data are integrated and analyzed on the corresponding overall dimensions of different storage types of the block chain, and the storage processing scheme corresponding to the storage type is dynamically managed according to the integrated analysis result, so that the security information storage autonomous supervision processing effect of different storage types is improved from the overall dimension.

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 discloses a short video information detection method, device and equipment and a storage medium, and relates to the technical field of network space security information detection.The method comprises the following steps that multi-modal information in a target short video is obtained, and multiple modal features corresponding to the modal information are extracted; performing feature alignment on the title features and other modal features to obtain a plurality of key features most related to the title; modeling the consistency among a plurality of key features most related to the title to obtain a first fusion feature representation and a second fusion feature representation; splicing the first fusion feature representation, the second fusion feature representation and the title feature to obtain a multi-modal fusion feature; and classifying the multi-modal fusion features to obtain a detection result of the multi-modal information in the target short video. According to the method, modeling is carried out based on feature alignment and semantic consistency, key information in the short video is better mined and fused, and the accuracy of an information detection result is greatly improved.

The invention relates to the technical field of intelligent locks, and discloses a video recording method and device of an intelligent door lock, computer equipment and a storage medium, the method comprises the following steps: when an event backtracking function of the intelligent door lock is in an enabled state, detecting a trigger event for the intelligent door lock; judging whether the trigger event has a backtracking requirement or not based on a preset analysis strategy; if the backtracking demand exists, recording the outdoor environment of the intelligent door lock based on the trigger event to obtain a recorded video; and when a playing condition corresponding to the trigger event is met, controlling the intelligent door lock to execute a playing operation of the recorded video. The problems that an existing intelligent lock depends on an application program to display safety information, so that key safety information cannot be effectively transmitted due to the fact that a user does not actively check the key safety information, and the practical function value cannot be fully exerted are solved.

This disclosure generally relates to securely pushing messages from an AF to a User Equipment (UE) in communication networks. Performed by a wireless device in a wireless network, the method includes receiving, from a first network element hosting an Application Function (AF), a message comprising one of: an AKMA (Authentication and Key Management for Applications) key identifier (ID) identifying an AKMA anchor key of the wireless device; or a set of parameters indicative of the AKMA key ID; and storing the AKMA key ID and an AF key associated with the first network element in a security context, wherein the first network element outside of a core network of the wireless network.