38 results about "Security awareness" patented technology

The invention relates to the technical field of tax data security, and discloses a data sharing privacy protection platform responding to tax digital requirements. The platform comprises a tax data privacy perception layer, a sensitive information positioning mapping layer, a cross-source data security fusion layer, a compliance sharing decision-making layer and an execution state feedback layer. The tax data privacy perception layer obtains multi-source tax information based on a dynamic differential privacy mechanism, generates an initial privacy risk heat map and segments a sensitive area; the sensitive information positioning mapping layer generates a data internal privacy distribution stereogram through a security perception array and time sequence analysis; the cross-source data security fusion layer establishes a space-time mapping relation and generates a privacy disclosure risk score; the compliance sharing decision-making layer converts the score into an executable sharing instruction; and the execution state feedback layer monitors data change, generates an evaluation index and dynamically adjusts a privacy protection strategy. According to the platform, the privacy protection of the whole tax data sharing process is realized, and the accuracy and dynamism of risk identification and strategy adaptation are improved.

The invention discloses a social engineering self-adaptive dynamic protection method based on post risk assessment, relates to the technical field of network security, and solves the problem that in the prior art, the aspects of employee security awareness modeling, multi-modal data fusion and personalized security policy recommendation still have obvious deficiencies. The method comprises the following steps: firstly, constructing an electric power post knowledge graph, and carrying out structured modeling on four entities of posts, permissions, assets and vulnerabilities and association relationships thereof to form a global semantic network; secondly, a post risk baseline model is established, a normal behavior mode is defined by quantifying inherent risks of posts and analyzing historical operation logs, and a static and dynamic combined risk reference is formed; and finally, designing a post exclusive feature extractor, fusing personal behavior data of the employees with semantic constraints and risk baselines of the knowledge graph, and generating highly personalized feature vectors, thereby laying a foundation for subsequent real-time monitoring of abnormal behaviors of the employees, quantification of safety consciousness and providing of differentiated protection.

The invention discloses an electric power safety knowledge testing method based on a large language model and enhanced retrieval generation. The method mainly comprises the steps of constructing a vector knowledge base, constructing a dynamic interaction generation workflow framework driven by a multi-role large language model, performing safety knowledge testing and quantifying the electric power operation safety awareness of a user. According to the invention, the problem with high scene adaptation degree can be dynamically generated in combination with the scene of the operation work order and the user interaction result, so that the test problem accuracy is improved; the quality of test content is improved through cooperative work of a multi-role large language model and in combination with an enhanced retrieval generation module; a dynamic adjustment strategy is implemented according to a user feedback mechanism, so that knowledge blind spots of the user can be effectively identified; the safety awareness of the user is quantified, targeted consolidation is carried out, and the electric power safety knowledge level of the user is improved.

The invention discloses a safe operation capability assessment method and system based on a multi-dimensional portrait, and relates to the field of operation capability assessment. The reliability of an assessment result is ensured through a multi-stage verification mechanism: a current operation video is input into a final operation specification degree mapping model for preliminary assessment; if the result is lower than the threshold value, triggering a subsequent process to carry out secondary evaluation; otherwise, the operator is required to work repeatedly and assess again; in the subsequent process, the error probability of the operator is calculated and compared with the non-standard proportion, so that the influence of external factors is eliminated, the safety awareness and capability of the operator are verified, and misjudgment caused by a single evaluation error is avoided; after an operator passes multiple rounds of verification, the system automatically judges that the safety capability of the operator reaches the standard, additional education is not needed, the management efficiency is remarkably improved, and meanwhile manpower resource waste caused by repeated training is reduced.

Systems and methods are described for recommendation of one or more security awareness workflows are described. One or more security awareness workflows may be deployed to deliver one or more remedial responses to one or more users in response to detection of one or more actions of the one or more users. An effectiveness of the one or more security awareness workflows are assessed and based at least on the assessment, one or more effectiveness metrics for the one or more security awareness workflows are determined. The one or more effectiveness metrics may represent the effectiveness of the one or more security awareness workflows. Based at least on the one or more effectiveness metrics, a recommendation of one or more security awareness workflow configurations may be identified.

The invention discloses a data processing method and device for VR interactive training of a cross-country container forklift. The method comprises the steps that VR interactive training data information of a user is acquired; the user VR interactive training data information comprises an action data set and an expression data set; processing the action data set to obtain a user action evaluation result; processing the expression data set to obtain a user emotion evaluation result; and according to the user action evaluation result and the user emotion evaluation result, performing personalized training suggestion and training content dynamic adjustment on the VR interactive training system. According to the invention, through efficient acquisition, deep processing and intelligent analysis of multi-dimensional data generated in the training process, the forklift driving operation level and safety awareness of trainees are accurately evaluated, the training result is fed back in real time, and the training strategy is dynamically adjusted, so that the quality and efficiency of the forklift driving VR interactive training are improved, and the training experience is improved. And the actual training cost and the safety risk are reduced.

A computer-implemented method of generating security awareness training samples may include receiving, structuring and storing information about a user of an organization into an organization knowledge base and selecting and fetching at least one training template, each including an electronic message template and a prompt template for a large language model. The prompt template(s) and the electronic message template(s) may then be specialized using the information about users of the organization stored in the organization knowledge base. The specialized prompt template(s) may then be submitted to a large language model artificial intelligence system. Textual content may then be received from the large language model responsive to each submitted specialized prompt template. A security awareness training sample may then be generated for each submitted specialized prompt template using the corresponding generated textual content received from the large language model and the corresponding specialized electronic message template(s).

The application discloses a safety education content pushing system and method for a construction site, and belongs to the technical field of safety education of the construction site. The safety education content pushing system comprises the following steps: listing education materials in a tree structure to generate a safety education library, and creating at least one dimension of identification tags for each education material to obtain an identification tag set; performing real-name authentication and numbering on workers to create work information files about the workers; creating a priority pushing model, obtaining pushing keywords required by the workers based on the work information files; mapping the pushing keywords to the identification tag set, matching identification tags having a mapping relationship with the pushing keywords in the identification tag set to obtain a temporary tag set; calling education materials corresponding to the temporary tag set in the safety education library to obtain to-be-pushed education materials, and pushing the to-be-pushed education materials to corresponding workers. The safety education content pushing system achieves efficient and high-precision education content pushing effect based on safety awareness and safety behaviors of the workers, greatly reduces learning time of the workers, and can also make up for part of defects of the workers.

The invention discloses a mail phishing test method and device, equipment and a storage medium. The method is applied to a phishing test system and comprises the steps that test configuration parameters used for configuring a phishing mail are received, a phishing test mail is configured according to the test configuration parameters, and the test configuration parameters comprise a test user group, a phishing domain name, a phishing page and a mail template; sending the phishing test mail to an office mailbox of a test object in the test user group, so that the test object performs a mail phishing test through the office mailbox, and collecting phishing test data fed back by the office mailbox; and generating a test analysis report of the mail phishing test according to the phishing test data. Multi-dimensional fishing test data are collected in real time, multi-dimensional analysis data are obtained, and the safety awareness of personnel is analyzed in various display forms from multiple aspects.

A system is provided.SOLUTION: A system for automatically generating security enlightenment content on the Internet, comprising: means for a user to input generation requirements; means for a server to receive and analyze the input requirements; means for selecting and activating a generative AI model based on the generation requirements; means for generating required text, images, and sounds by the generative AI model to create content; means for verifying and, if necessary, optimizing the generated content; means for sending the optimized content to the user; means for performing regeneration based on user feedback; and means for delivering the generated content.SELECTED DRAWING: Figure 1

This invention discloses a public security multimedia security monitoring system and method, including an information acquisition unit, an information identification unit, an information verification unit, an anomaly analysis unit, and an information output unit. This invention relates to the field of security monitoring technology and solves the technical problem of the inability to verify acquired information in a timely manner, thus reducing the real-time control of information. This invention identifies and verifies the acquired user information, compares the information in the database with real-time information to determine the correctness of the user information, and re-verifies users with erroneous information. It uses ID numbers and image information to monitor users' real-time information, thereby preventing users from falsifying information and improving the security of the work. Then, it directly generates warning signals for abnormal users and displays them to operators in a timely manner, enhancing the operators' security awareness.

The invention discloses a rolling equipment safety maintenance listing practical training assessment system and a practical training assessment method. The problem that rolling equipment safety maintenance listing operation practical training and assessment are lack of an integrated'three-party confirmation 'process intelligent practical training system is effectively solved. The rolling equipment safety maintenance listing practical training assessment system is formed by arranging the associated operation table, the power distribution cabinet, the rolling equipment and the like, the corresponding practical training assessment method is matched, a three-in-one mode of entity operation, virtual feedback and intelligent management and control is adopted, the forced operation sequence is achieved, the standard process of manual omission is reduced, and the practical training assessment efficiency is improved. The system achieves the dynamic simulation of accident consequences, improves the risk perception enhancement of safety awareness, achieves the automatic scoring and step judgment of a control system, saves the examination time, and improves the training efficiency.

1. The name of the design product: high-altitude falling simulation assembly (MQT071). 2. The use of the design product: a training device for simulating the scene of a person falling from a high place, allowing students to experience the danger of falling from a high place, and enhancing the safety awareness of the experiencing personnel. 3. The design points of the design product: the combination of shape and pattern. 4. The picture or photo that best indicates the design points: perspective view. 5. Other circumstances that need to be explained: the A area and the B area in the front view and the rear view are hollow designs, and the C area in the perspective view refers to the left side of the product, which is also a hollow design.

The invention relates to the technical field of data security training and evaluation, and discloses a holographic perception evaluation method and system for data security, and the method comprises the steps: constructing a security mapping model of multiple sensory channels, and mapping data security risk features to visual, auditory and tactile perception features; personalized perception intensity adjustment and semantic correlation optimization are carried out based on user cognition characteristics; dynamic simulation and interactive experience of known and unknown security threats are realized through a potential safety hazard simulation technology; establishing a unified cross-scene perception evaluation framework; according to the method, the limitation of a traditional single sensory channel is broken through, multi-dimensional cooperative transmission of safety knowledge is realized, the visual understanding and deep cognitive ability of a user on data safety risks are improved, and a systematic solution is provided for improving the overall safety awareness of an organization.

The present disclosure describes systems and methods for efficient reporting of data which includes personally identifiable information (PII) and which is collected and processed by a security awareness system. The data may be stored in a data storage system. The data may include a time stamp and queries of an historical nature may be supported. In the event that PII is removed from the data storage system, then the removal may propagate through all aspects of the data storage system, including the historical data.

This application discloses a method, apparatus, medium, and device for network security situation awareness. The method includes: acquiring key features related to network security; constructing an initial decision tree model based on a first training sample and the key features; optimizing the initial decision tree model to obtain an initial security awareness model; distilling a second training sample using a data distillation method; training the initial security awareness model based on the distilled sample; acquiring operational data of a power dispatch optical transmission monitoring system under the current situation; inputting the operational data into the trained security awareness model to obtain the security status of the power dispatch optical transmission monitoring system under the current situation; and directly judging the security status based on the operational data, thereby improving the accuracy of security event awareness. Furthermore, the use of data distillation technology to process the training sample yields more valuable high-level condensed samples, further improving the accuracy of security event awareness.

The invention provides a safety perception method and device, electronic equipment and a storage medium, and the method comprises the steps: determining an environment risk level based on the out-cabin environment information, and adjusting in-cabin monitoring parameters based on the environment risk level, thereby enabling the sensitivity of in-cabin monitoring to be matched with the real risk of the external environment; meanwhile, the driver state level is determined based on the in-cabin state information, and the out-cabin control parameters are adjusted based on the driver state level, so that the out-cabin sensing strategy can make up the possible insufficient sensing ability when the driver state is poor; the mismatching condition between the driver attention and the external environment risk can be accurately recognized, the problems that in-cabin and out-cabin information isolation causes safety strategy solidification and cannot adapt to a dynamic driving scene in a traditional scheme are solved, the accuracy and timeliness of safety perception are improved, and the driving safety is improved. And the driving safety in the intelligent driving scene is ensured.

This invention discloses a method and system for setting smart lock passwords based on the similarity of passwords from nearby users. The method includes: when a user registers or changes their password, obtaining the user's current geographical location information; searching a preset password database for all nearby users whose distance from the current geographical location is less than a preset threshold; determining whether at least one nearby user meets the distance requirement; if at least one nearby user is found, calculating the password similarity between the user's new password and the passwords of all the nearby users, and determining whether the password similarity is greater than a preset similarity threshold; if any password similarity is greater than the preset similarity threshold, prompting the user that the currently set or updated new password has security risks, and prompting the user to reset the new password. This invention aims to improve users' security awareness when setting passwords and guide users to create more complex and unique passwords, thereby improving the security of smart lock passwords.

The invention relates to the technical field of industrial safety production training, and discloses a full-chain safety training method, system and device based on VR practice and a medium, and the method comprises the steps: collecting the multi-source data of an employee, and processing the original multi-source data through a feature extraction algorithm; constructing a security knowledge-risk heterogeneous graph, fusing structured and unstructured data by using a graph neural network, and updating embedded vectors of employee nodes; generating a dynamic employee portrait based on the embedded vector of the employee node, generating a personalized training path according to the matching degree of the portrait and the post risk gap, and dynamically adjusting the path; dynamically arranging a VR training scene through a reinforcement learning engine, adjusting scene complexity in real time, and deploying a sensor in a VR environment to collect employee operation data; and analyzing employee interaction behaviors according to the multi-modal data, updating employee portraits and optimizing training paths. According to the method, the safety awareness and the emergency disposal capability of employees are improved based on a multi-dimensional perception interaction learning environment of the Internet of Things.

The application discloses a kind of reinforcement learning traffic signal control methods based on safety awareness aggregation, comprising: model is built;The model is trained, comprising: step one: obtaining historical state information;Step two: update first module, the first module includes state encoder, action-state encoder, overflow encoder and waiting encoder;Step three: update second module, the second module includes actor network, reward critic network, overflow cost critic network and waiting time critic network;Step four: repeat step one to step three until more than preset number, obtain the model after training;Obtain the observation information of current time, input the observation information of current time into the actor network after training, obtain current action to control traffic signal.The application integrates safety into environment interaction, state representation and policy learning three aspects, improve the safety of traffic.

This application discloses a method, apparatus, and device for intelligent assessment of operation and maintenance (O&M) behavior based on a large-scale model. By collecting multi-dimensional O&M behavior data and fusing it to generate a panoramic profile, and utilizing the deep semantic understanding capabilities of a large-scale language model, it achieves accurate assessment of O&M operation intent, proficiency, and risks. Compared to existing rule matching or shallow statistical methods, this invention can deeply understand the contextual semantics of operations, effectively distinguish between expert-level operations and novice errors, and significantly reduce the false alarm rate. Furthermore, this invention can not only identify risks but also diagnose specific skill gaps and automatically match training resources for personalized recommendations, constructing a closed-loop system of "assessment-diagnosis-empowerment," fundamentally improving the safety awareness and operational skills of the O&M team.

Aspects of the disclosure relate to dynamic cybersecurity event detection and training functions. A computing platform may monitor a plurality of user devices to detect a cybersecurity training triggering event. In response to the detection, one or more cybersecurity training session prompts may be generated and transmitted to one or more user devices. User input providing a response to the cybersecurity training session prompt may be evaluated for accuracy and scored for the cybersecurity training session. In some examples, an overall cybersecurity score for a user may be maintained and modified based on the score for the cybersecurity training session. One or more modifications may be identified and executed based on the scores generated.

Techniques for security vulnerability assessment of security-sensitive circuit designs are described. A placement of security-sensitive components of a design may be based on constraints related to how far apart a relevant set of security-sensitive components are allowed without consuming too much power and how to optimize the placement to minimize electromagnetic side-channel leakage or other security vulnerabilities. In one embodiment, a method may receive data that includes a representation of a design of an IC and may identify security-sensitive components of the design from the data. The method may determine a placement for the design based on constraints on a level of security vulnerabilities of the security-sensitive components and may perform a power simulation for the design based on the placement. The method may generate an assessment of the level of security vulnerabilities of the security-sensitive components based on the power simulation to adjust the placement for the design.

The object of the present invention is to provide a constriction assistance system that can optimize the safety and the productivity in a work at a construction site. Accordingly, the construction assistance system that has a safety construction assistance function that contributes to risk reduction in regard to a worker and a work machine at a construction site includes a server that collects operation information on the work machine deployed at the construction site, and a communication network that connects the work machine with the server. The server measures an actuation count of the safety construction assistance function, calculates a safety awareness level of the worker who works at the construction site on the basis of the actuation count, and delivers the safety awareness level to a receiving device.

The application discloses a kind of commercial complex compound emergency incident intelligent identification and joint disposal method and system, it is related to emergency handling technical field, this method is established according to area, floor and industry form Operating continuity unit, collects passenger flow, transaction, member residence, vertical traffic, security awareness and emergency facility availability data, generates collaborative boundary, operating continuity state vector and continuity rupture signature;When security awareness is abnormal or continuity rupture signature is established, generate incident candidate, lock compound accident chain after mechanism consistency verification and stable operation verification, determine joint disposal scheme based on recovery income, including safety action, traffic resolution action and operating intervention action, and according to disposal recovery record execution rule online, freeze or back out.This scheme is conducive to improving the adaptability of commercial complex compound emergency incident identification and linkage disposal.

This invention discloses a tactile training system and method for three types of misoperations in power systems, belonging to the field of power system safety training technology. It includes a simulated power distribution system, a status detection system, a misoperation simulation system, an intelligent control system, and an interactive training terminal. By simulating an electric arc through a controllable discharge device and achieving the effect of accidental operation through a protection device simulation module, combined with an audio-visual smoke system, it realistically simulates the consequences of three types of misoperations: incorrect protection side setting, incorrect protection side wiring, and accidental contact with live cables. This invention addresses the problem in existing technologies of lacking training equipment capable of realistically simulating the consequences of these three types of misoperations, making it impossible for trainees to intuitively experience the dangers of misoperations, and hindering the effective improvement of operators' safety awareness and operational skills. This invention can effectively improve power operators' awareness and ability to prevent and handle these three typical misoperations, thus preventing power accidents.

Aspects of the disclosure relate to dynamic cybersecurity event detection and training functions. A computing platform may monitor a plurality of user devices to detect a cybersecurity training triggering event. In response to the detection, one or more cybersecurity training session prompts may be generated and transmitted to one or more user devices. User input providing a response to the cybersecurity training session prompt may be evaluated for accuracy and scored for the cybersecurity training session. In some examples, an overall cybersecurity score for a user may be maintained and modified based on the score for the cybersecurity training session. One or more modifications may be identified and executed based on the scores generated.

The invention relates to an artificial intelligence power network security situation awareness and active defense system, which belongs to the technical field of power network security and comprises a situation evolution modeling module, an abnormal evolution detection module, a strategy intention generation module, a strategy evaluation and execution module, a response influence domain evaluation module and a self-adaptive optimization module. The situation evolution modeling module is used for constructing a space-time folding graph of a power network security state based on historical and real-time multi-source network data, and the abnormal evolution detection module is used for detecting the power network security state after receiving the space-time folding graph. After the strategy intention generation module receives the abnormal trend signal, the response influence domain evaluation module is used for evaluating the structural influence of the response instruction on the network state after the response instruction is executed, and generating an influence evaluation result; and the adaptive optimization module is used for generating a feedback record according to the influence evaluation result and the response instruction, and improving the security perception from state identification to trend prediction, thereby remarkably enhancing the perspectiveness of protection.

This invention discloses an industrial control network security protection system. In the field of network security technology, by extracting the continuous change characteristics of control state variables in industrial control communication and analyzing the sparse distribution trend of state mutations on the time axis, it dynamically determines the length of the observation time window matching the evolution characteristics of the current control behavior, thereby achieving effective identification of low-frequency, dispersed abnormal control behaviors embedded in normal communication. This method avoids the behavior fragmentation problem caused by fixed windows, enabling abnormal instructions that are originally distributed across cycles to be identified and associated within the same analytical field. It improves the detection capability of slow-paced, state-gradually shifting attacks without relying on complex rule bases or prior models, significantly enhancing the security awareness of industrial systems in covert control hijacking scenarios.