8 results about "Border Security" patented technology

The invention relates to a target positioning method based on radar photoelectric linkage guidance, and belongs to the technical field of edge-sea-air defense three-dimensional management and control of multi-source sensor fusion. According to the method, a dynamic calibration mechanism is provided, a real-time timestamp alignment and navigational speed calibration algorithm is introduced on the basis of traditional calibration, and radar measurement errors and coordinate conversion errors are effectively weakened; through an SAMURAI tracking algorithm of improved Kalman filtering, stable target tracking under shielding, appearance change and similar target interference is realized, and identity and position consistency is kept; the three-dimensional-to-two-dimensional projection conversion is adopted, the calculation precision of the pitch angle and the azimuth angle is improved, and the influence of radar latitude and longitude errors is reduced. Compared with an existing method, the method has the advantages that the precision and stability of joint positioning of the perimeter target in a complex environment are remarkably improved, the problem of target tracking jump is effectively solved, and the method has wide application prospects in scenes such as boundary security and protection and marine monitoring.

The invention relates to the technical field of information security, in particular to a detection method and system based on information security, and the method comprises the steps: obtaining multi-source heterogeneous data through a multi-source collection device, carrying out the time-space correlation analysis of the multi-source heterogeneous data through a feature fusion module, and generating a multi-dimensional feature vector; mapping the feature vector into a behavior sequence taking the security entity as a center, calculating a trust degree score for each security entity through a trust evaluation model, and outputting the feature vector corresponding to the security entity when the trust degree score is greater than a threshold value; according to the method, the feature vector is input into a pre-trained risk assessment model, a security threat level is output through the risk assessment model, and a system executes a corresponding early warning measure according to the security threat level. Instead, credibility scoring is carried out based on the deviation degree of entity behaviors and data, and the protection blind area of traditional boundary safety equipment is made up.

A method of installing a reusable security barrier is presented that allows quick installation and removal. In one embodiment, the method comprising providing precast concrete panels having a rectangular profile elevation, digging a trench having a length equal to or longer than the panel width, lifting and placing the panel such that a portion of the panel is inserted inside the trench and a portion extends vertically upward from the trench forming a barrier, with a narrow opening between the panels, and filling and packing the trench unfiled by the panels with a filler to provide a solid foundation. The method can comprise utilizing multiple panels placed side edge to side edge with their bottom inserted inside a trench to form a longer barrier. The method can further comprise removing the panels from the trench for reuse in a second site when the original security barrier is no longer needed.

The application belongs to the technical field of data security, and discloses a risk element dynamic identification method and system based on a knowledge base updating mechanism, which comprises the following steps: formally describing a data cross-border flow business process, and extracting knowledge data involved in the business process; coding the knowledge data to form structured information, and storing the structured information into a knowledge base; performing step-by-step coding and concept refining on the structured information in the knowledge base, screening out a core category and other categories, and an association relationship between the core category and the other categories; and identifying risk elements in the data cross-border flow business process according to the association relationship. The application can realize continuous improvement and intelligent identification of data cross-border risk elements, thereby improving the completeness and accuracy of risk identification, and enhancing the overall efficiency of data cross-border security management.

The invention discloses a multi-device cooperative space intelligent defense system and a control method thereof, and relates to the technical field of space intelligent defense, and the system specifically comprises a private domain injection device, a city linkage response device, a central control platform and an evidence storage module. According to the invention, a prevention and control closed loop from identification to stopping to tracing is realized through jet-type unique code marking, cooperative identification and tracking of unmanned equipment arranged in a city, task management of a central platform, and a non-lethal attack and judicial evidence storage module under manual authorization; the system integrates the functions of image recognition, behavior judgment, non-fatal intervention, evidence collection and evidence storage, supports relay scheduling and information collaboration among multiple devices, has a central AI control and manual authorization boundary mechanism and an automatic task scheduling and man-machine collaboration mechanism, can meet the intelligent defense requirements in multi-target and dynamic scenes, and is high in practicability. The method realizes real-time blocking and subsequent liability chain tracing, and is suitable for boundary security, key places, urban patrol and other scenes.

The application provides a kind of border patrol method and device of air-ground cooperation, electronic equipment and storage medium, wherein the method comprises: obtaining monitoring image, and transmitting monitoring image to patrol scheduling platform, monitoring image is based on ground camera cooperative acquisition obtained;Based on the initial identification result obtained by target identification of monitoring image to patrol scheduling platform, initial identification result is sent to command personnel, command personnel is used to confirm whether initial identification result exists anomaly;In the case where initial identification result exists anomaly, based on the distance between the preset position of machine nest and the suspicious area corresponding to initial identification result, determine task machine nest;Scheduling task unmanned aerial vehicle in task machine nest to suspicious area executes patrol, and determines patrol result.The method provided by the application cooperates with ground multi-party platform and unmanned aerial vehicle in the air, improves the accuracy and patrol efficiency of border emergency patrol, and further enhances the border security.

The invention discloses a security product deployment sequence verification method based on a protocol stack hierarchy and a boundary weight, and relates to the technical field of Internet security, a security product basic information knowledge base is constructed, the knowledge base stores product types, working modes, deployment modes and arrangement mode information of security products, and the security product basic information knowledge base is used for verifying the security product deployment sequence. The working modes comprise a routing mode, a reverse proxy mode, a transparent forwarding mode, a transparent proxy mode, an endpoint access mode, a mirror image monitoring mode, a software installation mode and an SaaS service mode, and the deployment modes comprise series deployment, side-hanging deployment, mirror image traffic deployment and endpoint access deployment. The method has the advantages that global topological linkage is enhanced, verification is carried out from the global perspective of boundary security, intranet security and host security, cross-level deployment conflicts and logic errors are recognized, and the integrity and effectiveness of the overall security architecture are ensured.

The invention discloses an infrared dense weak and small target detection method based on background semantics and cross-task feature interaction, and the method comprises the steps: firstly constructing a DenseSIRST infrared image data set with background semantic annotation, introducing a pixel-level sky background segmentation mask, and improving the perception capability of a model for a background context; then, a double-branch network architecture named BAFE-Net is provided, a detection and semantic segmentation collaborative learning mode is adopted, a feature channel with high task discrimination is extracted through a dynamic channel selection mechanism, and a feature adapter is introduced to realize explicit channel replacement between two tasks; therefore, the distinguishing capability of the model on a real target and a false alarm in a complex scene is enhanced. According to the method, excellent detection precision and recall performance are obtained on a DenseSIRST infrared detection reference data set, the false alarm rate can be remarkably reduced, and the method is particularly suitable for application scenes with multi-target dense distribution, complex background and false alarm interference in infrared images, such as the infrared vision fields of border security, airspace monitoring, night search and rescue, unmanned system navigation and the like.