25 results about "Security index" patented technology

The invention discloses a model adversarial mobility risk assessment method and system based on adversarial weight adjustment, and belongs to the field of adversarial attack and artificial intelligence intellectual property protection analysis. Comprising the following steps: generating an adversarial sample with high mobility through iterative optimization of a substitution model and the adversarial sample; and evaluating the adversarial mobility risk of the target model based on the generated adversarial sample by calculating a safety index. The invention aims to evaluate the security of the deep learning model for defending against the attack of the confrontation sample in the black box attack scene. According to the method, the flat local maximum value and the model smoothness of the adversarial sample are optimized by adaptively adjusting the parameters of the substitution model, so that the mobility of the adversarial sample is enhanced, and the substitution model does not need additional training data. The invention further provides a migration countermeasure attack safety index, and quantitative measurement is provided for model safety. According to the method, the vulnerability of the model to migration countermeasure attacks can be comprehensively analyzed, and researchers and engineers can be helped to design more effective defense strategies.

The invention provides a secret state data processing method and system supporting retrieval and credible verification, and the method comprises the steps: carrying out the encryption processing of each plaintext column in a plurality of plaintext columns according to a plurality of preset encryption algorithms, and obtaining a ciphertext column and a plurality of security index columns corresponding to each plaintext column; based on the plaintext column, the ciphertext column and a first target encryption algorithm, constructing a data possession proof of the encrypted database; when a retrieval statement input by a user is obtained, determining a target security index column corresponding to the retrieval statement, and retrieving the ciphertext column based on the target security index column to obtain a query result; wherein the query result comprises the target plaintext data obtained through decryption and the confidential database data possession proof corresponding to the target plaintext data; according to the method and the device, the efficient storage and retrieval of the structured data can be realized on the premise of protecting the privacy data.

To provide a method for determining a threat scenario using a generative AI.SOLUTION: A method includes: selecting a plurality of target API events from user's API event information obtained in a cloud environment, according to a predetermined condition; mapping each of the target API events to threat behaviors classified by type; determining at least one threat behavior set including at least one of the threat behaviors; determining at least one candidate scenario out of a plurality of reference scenarios stored in advance in a database, on the basis of the threat behavior set; calculating security index information by comparing the candidate scenario with the threat behavior set; determining an expected threat scenario out of the candidate scenarios on the basis of the security index information; and providing solution information to a user terminal on the basis of the expected threat scenario.SELECTED DRAWING: Figure 2

The invention relates to a method and computer program product for providing a neural network and system for classifying objects for a vehicle. The method according to the invention comprises the steps of providing a hazard and risk matrix for objects to be classified (S10), determining and assigning a safety weight to a misclassification depending on a risk rating (S20), determining and assigning a training weight to a misclassification (S30), and training a neural network by means of a plurality of iterations (S30). In this process, assigned training weights are dynamically adjusted to optimize a safety index, and the safety index is determined depending on misclassifications and assigned safety weights.

The invention provides a comprehensive security index evaluation method based on multi-task learning, and belongs to the technical field of network security management, and the method comprises the steps: synchronously collecting original data from a plurality of heterogeneous security data sources; a multi-task learning neural network model is constructed, and the model comprises a shared feature coding network for outputting shared features; the at least two heterogeneous task decoding networks are used for respectively mapping the shared features into preliminary security assessment results with different attributes; the fusion network is used for carrying out weighted fusion on the preliminary security assessment result to generate a comprehensive security index; using the multi-source security data set to train the multi-task learning neural network model; and inputting real-time security data of a to-be-evaluated system into the trained model, and outputting a comprehensive security index. The method has the advantages that the shared feature coding network can extract high-level feature representations with commonality from different data sources, and feature engineering dependence for a single data source or a single task is avoided.

A door lock security assessment method and a related device. The method comprise: sending a security assessment instruction to a door lock end, so as to trigger the door lock end to perform local security environment assessment to obtain a first security index corresponding to the door lock end; acquiring historical behavior data for the door lock end within a specified time period; performing security assessment analysis on the historical behavior data to obtain a second security index; receiving a third security index, which is sent by a control end; determining a security assessment result of a door lock on the basis of the first security index, the second security index and the third security index; and sending the security assessment result of the door lock to the control end.

The application provides a real-time security evaluation method and device. The method comprises the following steps: acquiring a monitoring data stream, and extracting security level information corresponding to each time point of all data blocks from the monitoring data stream; updating the weight change of the security index based on the security level information through a KernelSHAP method; incrementally updating an evaluation model by using the updated security index and weight, and predicting a security evaluation result by using the updated evaluation model; and determining a security evaluation result according to a preset decision threshold and the security evaluation result. By using the KernelSHAP method, the importance of the newly collected monitoring data stream is determined based on a wide learning system structure, the negative influence caused by the approximation error is reduced, the drift detection is combined with the adaptive and generated explanation ranking preference, and therefore the result of the real-time security evaluation task can be better predicted.

The invention discloses a risk prevention method, electronic equipment, a storage medium and a product, relates to the technical field of security prevention, is applied to a business integrated management system, and comprises the following steps: for any client system managed by the business integrated management system, determining an overall security score of the client system under each security index, detecting whether the performance of each key scene in the client system reaches the available base line of the system or not; judging whether the client system reaches a system security base line based on the overall security score; and under the condition that the client system does not reach the system safety bottom line and the system available bottom line, determining that the client system has potential risks, and carrying out switching-out processing on the client system. The technical problem of how to timely discover the potential risk of the system under the condition of ensuring that the system is safe and available is solved.

The invention relates to the technical field of office information publishing, in particular to an office information publishing method based on big data. The method comprises the steps of obtaining office information to be published, performing attribute sensitivity calculation on internal business data to obtain attribute sensitivity of the internal business data, constructing a sensitive feature attribute set for the attribute sensitivity based on a hierarchical clustering algorithm, analyzing association rules among attributes of the sensitive feature attribute set through an Apriori algorithm, and obtaining a sensitive feature attribute set; calculating mutual information amount among the attributes with strong association, and constructing an attribute dependency graph; calculating a security index of the external public data based on the external public data; and carrying out sensitive level grading on the internal service data based on the attribute dependency graph to obtain the sensitive level of the internal service data, and judging whether the office information to be published meets a publishing condition based on the sensitive level and the safety index. According to the invention, the leakage of office sensitive information can be prevented, and the security of office information release is improved.

The invention discloses an automobile financial transaction security management method, system and device based on a block chain technology, and relates to the technical field of data processing, the method comprises the steps that automobile financial transaction data and an automobile financial transaction network are acquired, a first time interval is matched, and the automobile financial transaction network comprises a plurality of block chain nodes; obtaining a first block chain node, obtaining a first data traffic, obtaining a second data traffic, obtaining a first suspicious traffic, and obtaining a first security index; obtaining a second time point, obtaining a third data traffic, obtaining a fourth data traffic, obtaining a second suspicious traffic, and obtaining a second security index; and obtaining a preset threshold value, obtaining a difference index, if the difference index exceeds the preset threshold value, correcting the first time interval, forming a second time interval matched with the automobile financial transaction data, starting early warning, and obtaining an early warning strategy according to the first safety index and the second safety index. The method has the advantages of accuracy, timeliness, dynamic adjustment and high resource utilization rate.

The invention relates to the technical field of website analysis, in particular to a website maintenance method and device based on security index calculation and a medium. The method comprises the following steps: when to-be-analyzed data of a target website is detected, determining a website overall evaluation value obtained by performing security index calculation on the target website according to the to-be-analyzed data and related information of the website overall evaluation value; and determining a security assessment suggestion corresponding to the overall assessment value of the website and the related information of the overall assessment value, and issuing the security assessment suggestion to the target website, so that the target website is improved according to the security assessment suggestion. According to the method and the device, the website security is quantitatively evaluated, so that the effect of accurately positioning the security problem of the website and the solution of the security problem is achieved, and the aim of ensuring the security and stable operation of the website is fulfilled.

The invention discloses a control method and device of an intelligent door lock and the intelligent door lock. The method comprises the following steps: when an unlocking trigger request is detected, obtaining identity information, a behavior mode and historical unlocking information of an initiator of the unlocking trigger request; according to the identity information, the behavior mode and the historical unlocking information, a safety index and a danger index of the initiator are generated, the safety index is used for quantifying the safety degree of the initiator, and the danger index is used for quantifying the danger degree of the initiator; adjusting the safety index and the danger index according to the evaluation result of the initiator to obtain a target safety index and a target danger index; and controlling the intelligent door lock according to the target safety index and the target danger index. The technical problem that in the prior art, an intelligent door lock system mainly depends on a biological recognition technology for identity verification, comprehensive analysis on behavior patterns and historical records is lacked, and then safety evaluation is not comprehensive enough is solved.

The invention belongs to the technical field of artificial intelligence, and relates to a security policy arrangement method and system based on a large model, and the method comprises the steps: S1, constructing a security component library which is provided with a plurality of security components; s2, constructing an environment state vector; s3, setting different priorities for each security index and forming a user preference vector; s4, constructing a multi-target reward function; s5, training a security policy arrangement model based on reinforcement learning; and S6, when a current user request is received, utilizing the trained security policy arrangement model to dynamically generate a security component calling sequence according to the current environment state vector and the user preference vector, and gradually examining and processing the current user request and candidate replies based on the security component calling sequence. According to the method, normal form transition from a static rule link to dynamic intelligent arrangement can be realized, so that a large model has high safety, high availability, low cost and self-adaptive capability.

The embodiments of this specification provide a secure index query method and device for protecting private data. Any of multiple parties obtains a first slice of the arithmetic share of a target index value to be queried; a first operation performed jointly by the multiple parties is used to convert the first slice into a second slice of Boolean share; each bit of the second slice is processed separately: the calculation interval of the i-th bit is determined based on n and the position index of the i-th bit; the string slice of the bit string of length n corresponding to the i-th bit is determined based on the calculation interval and the slice value of the i-th bit in the second slice; the string slice of the bit string corresponding to each bit of the second slice is processed using a second operation performed jointly by the multiple parties to obtain a slice of an identification string of length n; and a third operation performed jointly by the multiple parties is used to determine the slice of the query value corresponding to the position where the identification string value is 1, as the slice of the target query value corresponding to the target index value. This method can protect private data while being highly efficient.

The invention provides a data security assessment method and system, and belongs to the technical field of data security, and the method comprises the steps: obtaining financial system data; the financial system data is financial data stored in a financial system; the financial system data comprises current financial data and historical financial data; obtaining early warning financial data based on the current financial data and the historical data baseline; the early warning financial data is partial data in the current financial data; wherein the historical data baseline is determined based on historical financial data; performing clustering processing on the early warning financial data to obtain a target clustering result; performing risk assessment on the financial system data based on the obtained target clustering result to obtain a target safety index; the target safety index is used for representing the safety of the financial system data. According to the data security assessment method and system provided by the invention, the accuracy of financial data risk assessment can be improved.

According to the database security situation awareness method and system based on the multi-layer perceptron, security scores and security situation evaluation are calculated for multiple data sources and multiple complex security indexes, data serve as feature input of a multi-layer perceptron model, and real-time security situation awareness of a database is achieved. Quantitative analysis of key indexes such as identity authentication and access control, data integrity and confidentiality, system vulnerability and patch management, logs and audit, database performance and the like is combined with refined risk grade division of high risk, medium-high risk, medium risk, medium-low risk and low risk; the technical problems that in the prior art, a safety index system is incomplete, and a risk assessment result is rough are solved, and the accuracy and pertinence of database safety assessment are comprehensively improved.

The present invention provides a driving safety assessment method and system for a dynamic route, which compares the restriction information of each road section on the route to be assessed with the vehicle parameters of the transport vehicle to determine the value of the first safety index; uses an average vehicle speed prediction model to predict the predicted average vehicle speed of each road section in multiple future time slices; determines the predicted time and reference time of passing the route to be assessed according to the predicted average vehicle speed and the reference speed, and determines the value of the second safety index; collects negative events and their duration on the route to be assessed at the current moment; predicts the estimated arrival time of driving to the location of the negative event, and determines the value of the third safety index based on the estimated arrival time and the duration of the negative event; and determines the value of the total safety index by combining the values ​​of the first safety index, the second safety index and the third safety index. The route to be assessed is safety assessed by the value of the total safety index to ensure the reliability, timeliness and efficiency of transportation.

The invention discloses a guarantee degree analysis method for a water supply system, the water supply system is a system formed by a forebay and a water delivery pump group, the method comprises the following steps: collecting the water inflow of the forebay and the performance parameters of a plurality of water delivery pumps for measuring the availability of the water delivery pumps in real time, the performance parameters at least comprising the water delivery amount and the power; according to the water inflow and the performance parameters collected in real time, instantaneous supportability is obtained, and according to the water inflow and the performance parameters in the historical time window, theoretical supportability is obtained; and according to the instantaneous supportability and the theoretical supportability, obtaining a comprehensive supportability index for judging the guarantee degree. Through a plurality of parameters acquired in real time, the one-sidedness problem that the prior art depends on a single index is solved. Theoretical supportability is calculated in combination with data in a historical time window, future risks are predicted, and real-time disjunction with historical data is avoided. By integrating the instantaneous supportability and the theoretical supportability, a comprehensive supportability index considering the real-time state and the long-term trend is formed, and misjudgment is effectively reduced.

The application discloses an intelligent body running state security deviation real-time detection and self-trap stop method and system, and belongs to the technical field of intelligent body security monitoring. The application carries out sliding window statistical analysis on the intelligent body running time sequence behavior log, parallelly feeds normalized multidimensional security indexes into at least two independent detectors to capture sudden abnormality and persistent slight deviation, determines the security deviation grade through deterministic fusion, and finally executes corresponding control actions through a hierarchical self-trap stop state machine containing an irreversible absorption state. The application determines the security baseline through offline learning period, does not depend on probability distribution hypothesis, random variable or iterative optimization throughout the whole process, always produces the same output for the same input, and provides an intelligent body with a deterministic, auditable and non-bypassable running state security monitoring and self-trap stop scheme.

The application discloses a kind of based on power distribution network security situation Multistage fuzzy comprehensive evaluation method, it is related to power grid safety evaluation technical field, including acquisition power distribution network real-time operation data, environmental information and topological structure, combine history operation sequence to construct time series prediction model, output contains the dynamic safety margin sequence of key security index;Based on dynamic safety margin sequence, time attenuation cumulative operator is applied to the historical fuzzy membership degree of bottom layer security index, and the cumulative membership vector representing risk exposure intensity is generated;Call pre-built power distribution network knowledge graph, according to the semantic scene recognition of current operating state of power distribution network and the dynamic safety margin sequence, generate the multistage safety evaluation index subset adapted to current running context;Cumulative membership vector is mapped to the bottom layer security index of the multistage safety evaluation index subset, and the membership function with adjustable boundary parameter is constructed, and the fuzzy membership vector of bottom layer security index under preset comment set is output.

The invention discloses a power monitoring system network asset three-dimensional risk assessment method and system, and relates to the technical field of power monitoring system security, and the method comprises the steps: constructing a power monitoring system network asset comprehensive evaluation index system; risk assessment robustness is calculated according to the equipment safety indexes; calculating risk assessment robustness for the privacy security index; risk assessment robustness is calculated according to the operation safety indexes; calculating variances of the correlation degree sequence, the similarity sequence and the fluctuation degree sequence of the total index; and judging the total index risk degree. According to the method, the power monitoring system can be helped to better know the network security condition and the faced security threat, risk behaviors in the network and high-risk assets with high-risk ports, security holes, non-compliant configuration and the like can be found in time, so that a corresponding security protection strategy is formulated, the network security protection capability is improved, and the method is scientific, reasonable and convenient to implement. And safe and reliable operation of the power monitoring system can be effectively ensured.

The invention belongs to the technical field of password target range safety operation and maintenance, and particularly discloses and provides a password target range health degree prediction and fault self-diagnosis method based on big data, which comprises the following steps: constructing a high-fidelity digital twin fusing a multi-level architecture and an operation log, defining a collaborative optimization model containing endogenous safety indexes, and performing collaborative optimization on the collaborative optimization model; the intelligent decision agent is trained through reinforcement learning, a verification execution strategy is deployed in a physical target range, and strategy increment retraining is achieved through actual operation and new attack and defense data backflow. According to the method, the fitting capability of the digital twinborn body to a real network environment is enhanced, the time sequence consistency of the digital twinborn body is ensured, fine management of security risks is reflected, closed-loop feedback between a physical target range and the digital twinborn body is realized, and an intelligent decision agent can continuously learn and adapt to a new scene.

This application provides a method, system, equipment, and medium for the operation and management of smart security business in a park, relating to the field of smart security technology. The method includes: acquiring real-time monitoring data of various areas within the park; generating a first security index for each area based on the real-time monitoring data; constructing a state correlation matrix between the areas; calculating correlation coefficients between the areas based on the state correlation matrix; adjusting the first and second security indices based on the correlation coefficients; generating a delay impact factor based on historical time-series correlated event data of each area; adjusting the second security index based on the delay impact factor to generate a target security index for each area; and identifying areas where the target security index is less than a preset index as target areas and generating early warning signals for these target areas. The technical effect of this application is to improve the accuracy of security early warnings.

The invention discloses a data storage processing method and device, equipment, a storage medium and a program product. The method comprises the following steps: receiving encrypted data sent by a data uploading node; wherein the secret state data comprises encrypted data of data to be stored and a security index; storing the secret state data according to a hierarchical index structure; wherein credible credential data corresponding to the encrypted data is stored in a block chain, and a transaction value in the credible credential data is calculated based on the security index and the encrypted data; through the hierarchical index structure and block chain storage, it is ensured that the data cannot be tampered, the data is prevented from being maliciously tampered or destroyed, and therefore the authenticity and safety of the distributed storage data based on block chain technology support can be improved.

The application discloses a regional security evaluation method and device based on public opinion heat diffusion trend analysis, equipment, medium and product, and relates to the field of artificial intelligence. The method comprises the following steps: obtaining public opinion information on an Internet platform and performing data cleaning, feature extraction and format processing to extract formatted information features; classifying and scoring each piece of information based on the formatted information features to obtain a security evaluation score of an index to which each piece of information belongs; clustering each piece of information based on the formatted information features and sorting them in chronological order to identify a set of key events; calculating an event trend index for each key event in the set of key events; calculating an update amount of the influence of each key event on a regional security index based on the event trend index and calculating an updated regional security index; and performing regional security evaluation based on the regional security index before and after the update and the event trend index, which can improve the objectivity, timeliness and accuracy of regional security evaluation.