1268 results about "Security system" patented technology

The invention discloses an AI-based smart park multi-source data fusion method and system, and the method comprises the steps: generating a time-space aligned standardized data flow according to environment parameters, energy consumption waveforms, security signals and personnel trajectory data collected by a heterogeneous sensor network; generating a multi-modal fusion feature matrix based on the standardized data stream; according to the multi-modal fusion feature matrix, generating a three-dimensional twinborn body including the equipment state, the people flow density and the energy consumption hot spot in real time; inputting the three-dimensional twin into a multi-target constrained reinforcement learning algorithm, and fusing real-time data and prediction data to generate a Pareto optimal solution set; and based on the Pareto optimal solution set, generating a final instruction set for driving park equipment regulation and control, and triggering collaborative response of a security and protection system and an energy consumption system at the same time. According to the embodiment of the invention, intelligent upgrading of park management can be realized through cross-modal feature extraction, dynamic digital twin modeling and reinforcement learning optimization.

The invention discloses a smart park safety protection system and method based on smart video analysis and multi-mode integration, and relates to the technical field of smart park management. The system comprises a camera, an environment microphone and an access control terminal which are deployed in a park, an edge computing node is used for extracting structured video, audio and access control features, a central server realizes multi-modal space-time alignment through a self-calibration module, a multi-modal fusion module constructs a joint representation vector based on a low-rank tensor algorithm, and the joint representation vector is used for realizing multi-modal space-time alignment. And the security decision module identifies an abnormal event and triggers a response strategy in combination with a classification and anomaly detection model. According to the invention, multi-mode cooperative identification, high-robustness behavior analysis and intelligent response linkage are realized, and the real-time performance, accuracy and intelligent level of a park security system are improved.

The invention relates to the technical field of communication, in particular to a micro-segmentation-based multi-tenant zero-trust security system, which comprises a tenant network topology sensing module for acquiring network structures and service dependencies of tenants and generating a tenant-level network topology graph and a communication graph; a strategy rule automatic generation module generates a micro-segment access control strategy; the context-aware risk assessment module collects a user identity, an equipment state and a behavior track, and generates an access risk score; the strategy dynamic adjustment and application module updates the access control strategy; and the tenant isolation and zero-trust interaction module deploys a security sandbox to complete trust verification and isolation protection of cross-tenant requests. According to the method, the micro-segmentation strategy is generated by automatically identifying the service dependency boundary, the access control rule is dynamically adjusted based on the context, and refined isolation and risk-driven defense in a multi-tenant environment are realized in combination with the security sandbox and the zero-trust mechanism, so that the security and controllability of the system are remarkably improved.

The invention discloses a civil aviation airport security method and system based on multi-source perception and dynamic risk assessment, and the method comprises the steps: building a personnel-article-scene ternary relation model through collecting multi-source data such as video monitoring, face recognition, luggage scanning and sound signals; based on an abnormal matching mode of the model, dynamic risk assessment is carried out by combining real-time people flow density and historical event thermodynamic distribution, and a dynamic risk calibration map is generated; an identification strategy parameter is configured according to the risk level, a self-adaptive strategy set is formed and applied to the intelligent terminal, target identification and behavior tracking are achieved, and a security and protection system is automatically linked when a triggering condition is met; according to the method, the behavior-article-scene ternary relation model is constructed, so that multi-source data collaborative analysis is realized, the limitation of traditional single-mode detection is overcome, the abnormal behavior recognition accuracy in a complex scene is remarkably improved, and the false alarm rate is effectively reduced.

Techniques described herein can generate customized, user-based security response recommendations for users of security system(s), such as for security analysts tasked with performing responses to computing security threats. A user-based response recommendation engine can generate the user-based security response recommendations based on incident data associated with security incidents and based on historical user response data. Furthermore, user role inference techniques can optionally be used in conjunction with the user-based response recommendation engine.

The invention relates to the technical field of high-speed rail platform safety monitoring, and discloses a high-speed rail platform area intrusion detection and early warning alarm system, which comprises an acoustic and vibration sensor network deployed in a platform area and used for collecting environment signals in real time, the edge calculation unit extracts signal features and compares the signal features with a dynamically maintained environmental rhythm feature baseline to generate a detuning event mark, and the detuning mode analysis device identifies an abnormal mode through space-time correlation and triggers an alarm. According to the method, early perception of subtle anomalies is realized by constructing a multi-modal environment rhythm baseline, active perturbation injection and differential response analysis technologies are combined, the recognition capability of a silent target is remarkably improved, meanwhile, the monitoring continuity under an extreme working condition is ensured by using an elastic baseline adaptive mechanism, and the detection accuracy is improved. And a closed-loop security and protection system from passive sensing to active discrimination is formed.

The invention relates to the technical field of electronic information technology anti-counterfeiting, in particular to an electronic seal verification method based on a quantum true random number and an anti-quantum multi-dimensional dynamic code, which comprises the following steps of: generating a true random number by introducing a quantum random number generator, constructing a quintuple scene space, and fusing multi-dimensional data of a user, a seal, a file, time and a geographic position; an SPHINCS + anti-quantum signature algorithm is adopted, and block chain evidence storage is combined, so that a four-layer nested dynamic security system of quantum random injection, multi-source data binding, anti-quantum encryption and block chain evidence storage is formed. Meanwhile, a whole-process credible system from application, auditing to stamping and verification is constructed, compared with a traditional electronic seal, the quantum-attack-resistant electronic seal has remarkable breakthrough in the aspects of random number safety, quantum attack resistance, data fusion degree, tampering detection sensitivity and the like, and a credible electronic seal solution in the quantum era is provided for finance and other scenes.

The disclosed technology teaches a method for security monitoring in TLS or other certificate-pinned sessions by a cloud-based network security system. An endpoint routing client directs sessions through an inspection proxy by secure tunneling. A secure web gateway buffers encrypted packets in a new session with a cloud-based resource, detects a connection access request from a certificate-pinned application, requests and receives key extraction, and forwards keys to the security system. Traffic is buffered for decryption and forwarded without modification until the keys are available. The keys are applied to allow decryption and re-encryption, on a proxy basis, of traffic between the client and a cloud based system. The inspection proxy applies security policies, even to the TLS or other certificate-pinned session.

Provided in the present application are a server, a terminal and a security system. The server comprises an authentication and key management module, a secure multi-party computation engine and a secure-channel management module, wherein the authentication and key management module is used for performing identity verification on a terminal, generating a first private key corresponding to the terminal and a first public key corresponding to the first private key, and generating a first session key on the basis of a second public key of the terminal and the first private key; the secure multi-party computation engine is used for verifying fingerprint information of the terminal and cooperating with a plurality of terminals to perform identity verification on a server; and the secure-channel management module is used for establishing a secure channel with the terminal, encrypting communication data on the basis of the first session key, and using the secure channel to send the encrypted communication data to the terminal. The solution of the present application can effectively solve the security problem of communication between a terminal and a server, and has the advantages of high flexibility and a low cost.

The invention belongs to the crossing field of industrial control and edge computing, and particularly relates to an industrial personal computer data security dynamic protection method and system based on AI edge computing. Firstly, industrial control data encryption and standardization preprocessing are achieved through a hardware-level trusted execution environment; secondly, performing real-time anomaly detection on the encrypted data stream based on an AI model, generating a threat score by combining industrial control protocol feature analysis, and forming an edge layer intelligent detection capability; the authentication mode is dynamically switched based on the threat score, and self-adaptive strategy adjustment is realized in a fog layer; then optimizing edge resource allocation according to the threat index and the equipment load, and constructing a cloud elastic scheduling mechanism; and finally, a security system covering data encryption, real-time detection, dynamic protection and resource optimization is formed through grading component cooperation, and the method is suitable for real-time threat detection and self-adaptive response in an industrial internet scene.

The invention provides a remote control method and device for a security system, equipment and a storage medium, and the method comprises the steps: carrying out the feature extraction of security data of a fire alarm host, and obtaining a fire alarm scene vector; a preset linkage strategy library is matched according to the fire alarm scene vector, and a PTZ positioning instruction is obtained; controlling a camera to collect an alarm image based on the PTZ positioning instruction; based on a preset fire alarm analysis model, generating an alarm confirmation report according to the alarm condition image and the fire alarm scene vector; and notifying a plurality of preset user terminals to perform remote interaction according to the alarm confirmation report, and performing start-stop control on the fire-fighting equipment.

The invention relates to the technical field of power grid safety management, in particular to a digital twinning-based power grid control safety system and method.The digital twinning-based power grid control safety system comprises a power grid model unit, an intelligent recognition unit, a strategy making unit and a block chain cooperation unit. The method improves the operation safety and reliability of a power grid, optimizes the resource configuration of the power grid, reduces the energy consumption, provides detailed safety reports and risk assessment for the operation of the power grid, dynamically recognizes potential safety threats and abnormal behaviors, automatically generates a response strategy in real time, improves the overall safety of the system, and improves the safety of the system through the introduction of a block chain technology and the combination with digital twinning. According to the method, transparent information sharing and collaborative management among each level and each region of the power grid are realized, and through decentralized data storage and security guarantee, the power distribution networks in different regions can be ensured to be efficiently collaborative when facing network attacks or faults, and the response efficiency is improved.

Systems and methods are disclosed for autonomous security enhancement of a tenant network via a managed security service provider (MSSP) server comprising a processor and a memory, with information from a plurality of data sources, the method comprising querying a database or server, upon an encounter with an indicator of compromise (IoC), by a security system, to identify data sources of a plurality of data sources, wherein the data sources include information on the IoC; generating, via the processor, an IoC threat score for the IoC; generating, at least one actionable security enhancement notification based on the IoC threat score; and deploying an automated security response that can comprise displaying the IoC threat score and an actionable security enhancement notification to a user, allowing triggering or disabling of at least one action based on the single IoC threat score.

The invention discloses an Internet of Things equipment monitoring data stream processing method and system. The method comprises the following steps: step 1, collecting and preprocessing multi-source heterogeneous data; step 2, dynamic routing distribution; step 3, edge calculation processing; 4, performing real-time feedback regulation and control; 5, performing anomaly detection and fault tolerance; step 6, data persistence storage; step 7, performing multi-dimensional analysis; and step 8, security enhancement processing. According to the method, intelligent distribution of data streams is realized through the dynamic routing engine, optimal nodes are matched, and resource waste is reduced; the edge computing node cluster completes preliminary screening and filtering, reduces core pressure, adopts an active-active storage subsystem, combines hot and cold storage, reduces cost and guarantees access performance, a safety protection module constructs a full-link safety system, and cooperates with a dual-mode redundancy architecture to improve system availability and fault switching second-level response.

A cloud security platform configured to protect a cloud environment is described. The cloud security platform features a cloud analysis logic and cloud security system. The cloud analysis logic is configured to (i) identify one or more security threats associated with a code submission for evaluation and (ii) generate a message including information associated with the one or more security threats. The cloud security system is configured to determine a difference between the one or more security threats associated with the code submission and at least one security threat associated with a prior code submission or production code that pertains, at least in part, to the code submission. The difference causes the cloud security system to refrain from release of code included in the code submission as production code.

The invention discloses a railway pedestrian warning system and method based on an improved YOLOv7 algorithm, and the method comprises the steps: dynamically dividing a warning region according to the GPS positioning of a train and a train timetable, and obtaining a plurality of regions; performing pedestrian recognition on the monitoring area by using a high-resolution camera deployed with a pedestrian target detection model to obtain pedestrian coordinates; wherein the pedestrian target detection model is constructed based on an improved YOLOv7 algorithm; calculating pedestrian dynamic potential energy fields and potential energy gradients in real time according to the pedestrian coordinates and the plurality of areas, and obtaining risk scores according to the potential energy gradients and pedestrian motion vectors; and performing graded early warning and voice warning on the pedestrians according to the risk scores. The invention relates to the technical field of railway security and protection, and solves the technical problems of insufficient detection precision, high false alarm rate and insufficient dynamic risk quantification capability of an existing security and protection system in a complex inter-city railway scene.

The invention provides an abnormity early warning security system and method based on cross-modal semantic retrieval, and relates to the technical field of public security, and the system comprises a video collection and frame sampling module which is used for extracting key frame images from a real-time monitoring video stream according to a preset frame interval and storing the key frame images to an object storage system; the target detection module adopts a YOLO model to execute instance-level target detection on the extraction frame, and generates a structured detection result containing a target position, a category and confidence; the semantic vector storage and structured warehousing module packages the standardized metadata of the image frame and the semantic vector generated by the CLIP into structured data, and stores the structured data into a high-performance vector database; and the semantic retrieval and reverse query module receives a natural language query instruction to generate a semantic vector, and realizes cross-modal retrieval of historical monitoring images through vector similarity matching. According to the invention, a set of exception security system with real-time perception capability, semantic understanding capability and cross-modal retrieval capability is constructed.

The invention provides a smart campus security early warning management method and system, and relates to the technical field of smart campus management, and the method comprises the steps: extracting the security demand information of students in a campus from campus security data; determining interaction early warning attributes in a target campus security supervision period through security deployment paths and track association levels in historical security event libraries of different supervision areas of the target campus; determining a security offset node of each supervision area in the target campus according to the security risk index, and determining a correction behavior tag of the student in the target campus according to the security offset node and the interactive early warning attribute; and managing and controlling the safety behavior characteristics of the students in the target campus according to the corrected behavior labels, and generating early warning feedback information of the activities of the students in the target campus. According to the application, fusion deduction can be carried out on the association relationship between the student behavior track and the security resource dynamic demand, so that the response accuracy of the campus security system is improved.

The invention relates to safety compliance evaluation, in particular to a safety compliance evaluation system and method based on a multi-modal large model, and a functional module cluster, which are used for managing each functional module in the system, supporting cross-modal consistency detection and comparing answer consistency under different modals. The self-developed security system is responsible for execution of an assessment task, including resistance test enhancement and built-in multi-granularity data variation strategy, improves assessment robustness by simulating a real attack scene, realizes end-to-end automation from data generation, tested model test to risk assessment, supports configurable parameters and reproducible results, and has the advantages of high reliability and high reliability. The self-iteration and version management of the evaluation model are realized, and the self-iteration mechanism is deeply combined with a compliance label system, so that the risk identification capability under legal, ethical and industrial specifications can be continuously optimized; according to the technical scheme provided by the invention, the limitation that evaluation can be carried out only under a single mode and a single rule in the prior art can be effectively overcome.

The invention provides an electric power system cross-source safety intelligent monitoring and dynamic response method and system based on mimicry defense, and relates to the technical field of electric power system network safety. According to the method, multi-source data are acquired by deploying an acquisition agent and a sensor and are encrypted and transmitted, parallel analysis and threat judgment are realized by utilizing a heterogeneous executor pool and dynamic scheduling, an attack chain is identified by combining cross-domain association modeling, disposal is performed according to grades, credible recovery is supported, and reinforcement learning and federated learning are assisted to optimize a strategy and resource allocation. And lightweight adaptation is realized through intensity control in a resource limited scene, a closed-loop safety system covering data acquisition, threat analysis, dynamic disposal and continuous evolution is formed, and the detection accuracy, response efficiency and robustness of a power system are improved.

The invention discloses an intelligent security alarm system and method based on wireless networking, and relates to the technical field of Internet of Things and intelligent security, and the system comprises a security data collection module, a security feature extraction module, a security anomaly detection module, a security alarm module and an intelligent security management module. The security and protection data acquisition module acquires human body infrared, environmental sound and three-dimensional vibration data, extracts security and protection characteristics, detects movement and sound abnormity, constructs an alarm model, carries out graded alarm, issues information through a wireless technology, and displays regional security and protection event distribution through a thermodynamic diagram. According to the invention, wireless acquisition and intelligent fusion of multi-modal security data are realized, the accuracy and real-time performance of anomaly detection are significantly improved, security event distribution is visually reflected through hierarchical alarm and thermodynamic diagram display, rapid response and decision are facilitated, the false alarm rate is reduced, system deployment and maintenance are simplified, and the system reliability is improved. And the intelligence and practicability of the security and protection system are enhanced.

The disclosed technology teaches a method for security monitoring in TLS or other certificate-pinned sessions by a cloud-based network security system. When a security condition is detected in the decrypted packets, alerts are generated for the client device. The method involves injecting a message into the session using keys extracted by the cloud-based resource for encryption. Some implementations utilize an inspection proxy and an endpoint routing client for secure tunneling. A secure web gateway buffers encrypted packets in a new session with a cloud-based resource, detects a connection access request from a certificate-pinned application, requests and receives key extraction, and forwards keys to the security system. The secure web gateway applies the keys to systematically encrypted traffic, decrypts packets, and relays ongoing session traffic between the security system and the client device via the inspection proxy, which applies security policies during the process.

The invention relates to the technical field of intelligent manufacturing and industrial Internet of Things, in particular to an intelligent factory equipment safety management system and method, and the system comprises an identity authentication module, a dynamic safety interaction module, an intelligent monitoring response module and a self-adaptive optimization module. An identity authentication module; through fusion of multi-dimensional information authentication, block chain decentralized storage, intelligent algorithm behavior analysis, encrypted communication and fine-grained authority control, multi-source data threat detection and reinforcement learning driven strategy optimization, a whole-process security system is constructed. The method comprises the steps of identity authentication, security interaction, monitoring response and adaptive optimization. The problems that in a traditional industrial scene, equipment identity authentication is fragile, data transmission is not safe, threat response lags and strategies are staticized are solved, high-safety authentication, dynamic encryption communication, real-time threat response and strategy self-optimization are achieved, and the equipment safety protection capacity and the system intelligence level are improved.

The invention belongs to the technical field of network security, and relates to a terminal security access control method and device, computer equipment and a storage medium, the method comprises the following steps: deploying an infrastructure for terminal security access, the infrastructure comprising a client, a security system and a server component; the method comprises the following steps: performing initial registration on terminal equipment, and realizing unique binding of a terminal identity and loading of a basic security policy by acquiring an equipment fingerprint, issuing a certificate and configuring a policy; the user identity and the equipment credibility are verified in real time through a multi-factor dynamic authentication mechanism; through signature verification and encrypted transmission, application and network communication authentication is carried out, and application legality, communication channel security and operation environment credibility are ensured; and after the authentication is passed, trusted connection is established, fine-grained authorization is implemented, and security isolation of a service layer is realized through dynamic token and API management and control. The problems that in existing terminal access control, the authentication dimension is single, the authorization granularity is rough, and dynamic management and control are lacked are effectively solved.

The invention discloses an SM2 collaborative signature and encryption and decryption system and method fusing anti-quantum characteristics, and relates to the field of cryptography and information security. According to the method, an anti-quantum cryptographic algorithm and a national cryptographic SM2 cooperative computing framework are deeply integrated, and a key security system is constructed: SM2 sub-private keys, anti-quantum key pairs and public keys are acquired and generated through an anti-quantum algorithm software and hardware enhancement module, and the private keys are encrypted and stored and are regularly alternated; on the basis of anti-quantum collaborative signature, encryption and decryption modules, an anti-quantum verification mechanism is embedded, and data is transmitted in combination with a national secret TLCP protocol, so that signature, encryption and decryption operations are completed; the equipment integration and dynamic security control unit monitors a security state, calculates a threat index to generate a protection strategy, and dynamically switches a security mode, so that the problems of insufficient security, vulnerability to attacks and data tampering of a traditional SM2 algorithm under the threat of quantum computing are effectively solved; and the long-term anti-attack capability and the operation reliability of the equipment in a high-security demand scene are remarkably improved.

The invention provides a digital twin smart park security and protection management system based on artificial intelligence, and relates to the field of security and protection management, and the system comprises a multi-mode sensing network which is used for collecting park environment data through a multi-mode sensor network, and carrying out the preprocessing of the data, and obtaining an environment data set; the digital twin modeling module is used for constructing a park three-dimensional virtual model based on the environment data set; the semantic alignment module is used for defining a dynamic security semantic rule based on the three-dimensional virtual model and carrying out semantic alignment of multi-modal features on the environment data set; the threat assessment module is used for performing threat assessment on the aligned semantics based on a knowledge graph and a Bayesian network; and the resource scheduling execution end is used for generating a disposal plan according to the evaluation result and realizing security response through an execution terminal. The method is used for solving the problems of information isolated island, response lag, high false alarm rate, fuzzy situation awareness and the like of a park security system in the prior art.

Systems and methods for source chain management with identity-based tokens and enhanced security are disclosed. A processing system receives input that includes a decentralized identifier (DID) uniquely associated with an entity. The processing system invokes a smart contract deployed on a distributed ledger to mint a non-transferable identity-based token permanently linked to the DID. Metadata generated for the token includes cryptographic references to a hierarchical source chain structure stored in a decentralized data storage system, along with cryptographic verification data. Events associated with the DID are memorialized by appending granular event details, including timestamps, data changes, and origin identifiers, into the hierarchical source chain. Authorized access to event details and tokens is provided via an authenticated interface that securely retrieves and reconstructs encrypted data shards distributed across decentralized nodes, enhancing data security, immutability, and verifiability in decentralized environments.

AI-powered data breach detection and prevention system that includes: a threat monitoring module for continuous analysis of network traffic, system logs and user activities; an AI-powered anomaly detection module that uses machine learning to detect threats, including zero-day attacks and insider threats; a behavioral analysis module that tracks user authentication, access patterns, and privilege escalations; an automated incident response module that isolates threats, blocks unauthorized access, and alerts security teams; a threat intelligence module that integrates global cybersecurity databases for proactive risk mitigation; a multi-layered security system with endpoint protection, encryption and role-based access control; a privacy-preserving mechanism that uses homomorphic encryption and federated learning to protect sensitive data; a compliance and audit module that ensures compliance with cybersecurity regulations.

Implemented within a cyber security appliance, a non-transitory storage medium configured to store software that, when executed, conducts data loss prevention evaluation of an email message to protect against exfiltration of sensitive data from an enterprise. The software includes an email protection module and high availability (HA) fail-open control logic. The email protection module includes email threat detection logic to analyze content associated with an outbound or lateral email message for potential data loss characteristics. The HA fail-open control logic is configured to (i) detect operational failure of the email protection module or intake disruption of email messages via an Application Programming Interface (API) providing access to the email protection module and (ii) redirect the email messages to HA cloud infrastructure pertaining to the enterprise for temporary storage and subsequent release of the redirected email messages upon detecting the operational failure or the intake disruption.

The invention discloses a vulnerability closed-loop disposal method and system based on intelligent collaboration, and belongs to the technical field of information security management. Vulnerability data and disposal information in a plurality of independent security systems are collected, and a multi-dimensional vulnerability semantic model is constructed; constructing a state perception graph based on a semantic model, extracting candidate state paths, and constructing a time sequence closed-loop prediction model in combination with a shortest closed-loop path and a historical track; according to a vulnerability influence range, a service dependency chain and a prediction path key node, adaptively dividing responsibility affiliation, generating a dynamic disposal responsibility graph and realizing automatic assignment; combining the node response capability and the task saturation, dynamically calculating the priority and scheduling the processing task; monitoring an actual disposal behavior, correcting an edge weight of the state diagram in real time and updating the model; according to the method, the whole-process intelligence, collaboration and dynamic evolution of vulnerability management are realized, and the processing efficiency and the prediction precision are improved.