8 results about "Behavior rule" patented technology

The invention relates to the technical field of network security and data protection, and discloses a data leakage prevention method and system based on user behavior perception, and the method comprises the steps: obtaining historical operation data, and constructing a personalized behavior reference library; monitoring a current access behavior in real time by sliding a time window, calculating a deviation degree and triggering anomaly detection; performing multi-level feature analysis on the abnormal behavior and calculating a comprehensive abnormal score; dynamically adjusting the access authority according to the score, recording an abnormal behavior and carrying out relevance matching; optimizing the reference model through feedback learning; and evaluating the credibility and the risk level based on an accurate modeling result, and adaptively adjusting permission configuration. According to the method, the user behavior rule can be accurately captured, the data leakage risk can be efficiently identified, the access permission can be dynamically adjusted, the false alarm rate can be reduced, adaptive protection can be realized, and data security and business smoothness can be guaranteed.

The system according to this embodiment aims for the AI ​​to comply with ethical guidelines and constraints and to exercise self-control. [Solution] The system according to the embodiment comprises a listing unit, a rule setting unit, a reward / penalty unit, a feedback unit, and an ethical judgment unit. The listing unit lists permitted and prohibited actions. The rule setting unit sets actions that are permitted only under specific circumstances. The reward / penalty unit rewards desirable actions and penalizes undesirable actions. The feedback unit adjusts the algorithm based on the AI's actions. The ethical judgment unit makes ethical judgments.

The application relates to the technical field of industrial control safety, in particular to a PLC runtime abnormal behavior identification method and system based on a behavior model, which comprises the following steps: S1, in the PLC program running process, a behavior monitoring module performs real-time monitoring and preliminarily judges abnormal behavior; S2, normal behavior and abnormal behavior are filtered out respectively according to the monitoring results of the behavior monitoring module, and behavior rule extraction is performed on the behavior monitoring module; and S3, behavior modeling is performed based on the extracted behavior rules, normal behavior model generation or update of behavior rule information files is performed on the detected normal behavior, and abnormal behavior model learning of abnormal characteristics, rapid abnormal identification and measure processing are performed on the detected abnormal behavior. The application uses a data model to describe the normal behavior model of the control behavior and the process behavior through the dependent relationship of the normal input and output data of the control and controlled process, so that the intrusion behavior can be accurately identified, and active defense can be performed.

An information security monitoring system can import indicators of compromise (IOC) definitions in disparate formats from third-party source systems, convert them into editable security definitions in an internal system format, and provide a user interface for composing or editing these security definitions with enhancements, including complex security definitions such as those having a nested Boolean structure and / or those that reference one or more security definitions, a behavioral rule, and / or a vulnerability description. One or more whitelists can be added to handle exceptions. Each composed or modified security definition is then compiled into an executable rule. The executable rule, when evaluated, produces a result indicative of an endpoint security action needed in view of an endpoint event that meets the composed or modified security definition.

The invention discloses a conflict resolution method and device based on flow node hierarchical management and a medium, and relates to the technical field of software development, the method comprises the following steps: defining a behavior rule and a control rule of a low-code business form to obtain metadata definition data of the low-code business form; performing rule coverage of process nodes on the metadata definition data to determine a process rule set; obtaining a current running context, and performing rule configuration on the current running context based on the flow rule set to obtain a current multi-source flow rule; according to the current multi-source process rule, constructing a rule conflict dependency graph, and performing field pre-definition processing on the rule conflict dependency graph to determine a pre-definition resolution strategy; and based on a predefined resolution strategy, through rule influence degree prediction and resolution strategy recommendation processing, obtaining a conflict-free element state set. According to the method, the technical problem that in the prior art, a low-code platform cannot perform conflict resolution through context sensing capacity is solved.

The invention provides an authority authentication method, a user terminal, a learning platform, equipment, a medium and a program product, which can be applied to the technical fields of artificial intelligence technology and financial science and technology. The method is applied to a user terminal and comprises the following steps: performing feature extraction on a first interaction behavior of a target object to obtain a first behavior feature of the target object; according to the first behavior rule, performing compliance identification on the first behavior feature to obtain a first identification result; under the condition that the first behavior recognition result represents that the first behavior does not meet the first behavior rule, a second behavior feature determined based on a second interaction behavior of the target object is sent to the learning platform, and the learning platform performs compliance recognition on the second behavior feature according to the second behavior rule to obtain a second behavior recognition result; and receiving a second behavior recognition result sent by the learning platform, and determining an authority authentication result for the target object under the condition that the second behavior recognition result represents that the second interaction behavior meets the second behavior rule.

The invention discloses a behavior prediction method fusing behavior rules and deep learning, and the method comprises the steps: obtaining a behavior video in which human body plane coordinate position information is embedded, and carrying out the preprocessing of the behavior video, and obtaining a video frame; carrying out human body appearance and key point feature coding on the video frame in combination with a long-short-term memory neural network and a convolutional neural network; performing surrounding environment and human ring interaction feature coding on the behavior video frame by using a long short-term memory neural network; cascading all the feature codes to obtain a feature fusion code; generating a movement prediction track of a person by using a long-short-term memory neural network to obtain a movement track generation network of the person; converting the behavior rule model of the person, which is kept unchanged under time translation transformation, into a computable behavior rule model; integrating the computable behavior rule model into a human movement track generation network; and predicting a behavior category by using a full-connection neural network. According to the method, the model training data overhead can be reduced, and meanwhile, relatively high behavior prediction accuracy can be realized.

One or more embodiments of the present disclosure provide a business processing method and device, electronic equipment and storage medium. The method comprises: in response to receiving a rule invocation request, parsing scenario information and activity information according to the invocation request; invoking data rules and / or behavior rules corresponding to the scenario information and the activity information from a rule library to a rule engine; the data rules and the behavior rules are stored in the rule library in layers according to global common or regional difference attributes; determining a data object of the activity according to the data rules and the behavior rules, and invoking business data corresponding to the data rules and the behavior rules according to the data object; executing the data rules and the behavior rules based on the business data to obtain an execution result of the business.