10 results about "Attack time" patented technology

Provided are an audio peak limiting system and method, which, by setting a moving maximum window to drive gain calculation, and in combination with matching a moving maximum window length to a delay duration of an audio input signal, suppress a risk of overshoot while enabling a user to flexibly adjust a suitable attack time, and result in a smoother gain curve and reduce distortion in dynamic range processing, thereby achieving a more natural auditory perception.

The invention discloses an information security encryption system, which comprises a data acquisition and preprocessing module, an attack situation feature extraction module, a dynamic risk assessment module, a decision execution module and a model training and self-adaption module, the data acquisition and preprocessing module generates a structured attack log containing attack time, attack type and attack interval; the attack situation feature extraction module is used for receiving the structured attack log, calculating a duration distribution weight by adopting a robust statistical method based on an attack interval duration, calculating an attack continuous weight and generating an attack credible weight in combination with an effective transmission quantity and a data entropy value, and calculating attack complexity based on a time sequence clustering result at an attack moment; and the dynamic risk assessment module is used for calculating time period attack intensity according to the attack credible weight and the attack complexity, calculating an attack intensity change index, performing fusion calculation on the attack intensity change index, a key updating time difference risk and a to-be-transmitted data volume risk, and outputting a bearing risk coefficient.

The invention discloses a network intrusion tracing method and system based on behavior analysis, and relates to the technical field of network security. The method comprises the following steps: S1, constructing an attack activity propagation graph and calculating an attack propagation coefficient between nodes; s2, according to behavior data and attack propagation coefficients of each node in the attack activity propagation graph, calculating behavior pulse factors of the nodes, and determining attack participation nodes; s3, calculating a time propagation coefficient of an attack path and constructing an attack time trajectory according to interaction time difference characteristics and behavior pulse factors among the nodes; s4, according to the flow rate, the attack propagation coefficient and the time propagation coefficient between the nodes, calculating a traceability flow overflow index, and generating a potential attack source set; and S5, calculating an attack intensity adjustment coefficient according to the traceability flow overflow index and the flow rate, and triggering a defense strategy response mechanism based on the attack intensity adjustment coefficient. Precise traceability and real-time defense are realized through multi-dimensional behavior analysis, and the network intrusion response efficiency is improved.

Provided in the present disclosure are a security deduction method and apparatus, and a network device and a readable storage medium, which are applied to the technical field of security. The method comprises: on the basis of network state information of a twin network and a plurality of preset attack events, obtaining attack times at which the attack events execute successful attacks on the twin network before a first time; on the basis of the network state information and the attack times, determining each attacked entity corresponding to the successful attacks before the first time; performing superposition analysis on attack effects generated by the successful attacks on each attacked entity, so as to obtain attack assessment information; and on the basis of the attack assessment information, adjusting the network state information of the twin network and / or the attack events, and performing security protection configuration on the twin network. The method can solve the problem whereby, in security deduction methods in the prior art, deduction / simulation is inaccurate and the security drill effect of a service system in a real network environment cannot be achieved.

The invention provides an Internet of Things attack tracing method and device, equipment, a storage medium and a product. Comprising the following steps: acquiring an attacked Internet of Things device and an attack time window according to an Internet of Things device log; collecting multi-source communication data, and judging whether a single-hop Internet of Things attack link exists or not according to the multi-source communication data; if it is judged that the single-hop Internet of Things attack link does not exist, a communication graph of the attacked Internet of Things equipment is constructed according to the multi-source communication data; in the communication graph, taking the attacked Internet of Things equipment as a starting point, and obtaining a plurality of candidate multi-hop Internet of Things attack links; obtaining a credibility value of each candidate multi-hop Internet of Things attack link; and determining the candidate multi-hop Internet of Things attack link with the highest credibility value as a final multi-hop Internet of Things attack link. Wherein an end point in the final multi-hop attack link of the Internet of Things is an attack end of the Internet of Things. According to the method provided by the invention, the accuracy of attack tracing in the Internet of Things environment is improved.

The invention provides a data processing method and device, equipment and a medium. The method is executed by an aggregation node, the aggregation node and a plurality of terminal nodes form an equipment network, and the method comprises the following steps: acquiring aggregation data sent by the terminal nodes; determining first security data of the aggregated data based on a data source and / or a data type of the aggregated data; determining second security data of the terminal node based on the historical data traffic and historical attack times of the terminal node and the connection times of the terminal node and the sink node; determining a security level of the aggregated data based on the first security data and the second security data; and obtaining the security level of each storage device, determining a target storage device corresponding to the converged data based on the security level of the converged data and the security level of each storage device, and storing the converged data through the target storage device. According to the technical scheme of the invention, the security and adaptability of aggregation data storage are improved.

The embodiment of the invention discloses a training method of an attack behavior prediction model, an attack behavior prediction method and related equipment, and belongs to the technical field of network security processing. The method comprises the following steps: extracting a plurality of attack entities from original alarm information, and determining an attack event between any two attack entities and attack time corresponding to the attack event; inputting a plurality of sample attack sequences determined by the attack entity, the attack event and the attack time into the attack behavior prediction model, and outputting a predicted attack sequence after shielded information in each sample attack sequence is recovered; and determining a sequence loss value according to each predicted attack sequence and the corresponding tag attack sequence, and performing iterative training on the attack behavior prediction model according to the sequence loss value to obtain a trained attack behavior prediction model which is used for predicting the next attack behavior of the generated target attack behavior to obtain a predicted attack behavior. According to the invention, the accuracy of completely predicting all attack behaviors can be improved.

The invention discloses a network security early warning method and system based on multi-source data, relates to the field of power grid security, and solves the technical problems that in power grid security management, it is difficult to carry out prospective early warning on security attacks suffered by power grid equipment, and potential situation reminding of attack early warning by spatial geometric features of attackers is neglected. According to the method, the threat prediction model is established based on the historical attack record, and the time range and potential propagation equipment of the next attack after the current attack are identified based on the threat prediction model; determining an importance factor of the equipment based on the basic information, and determining a severity factor of the attack based on the attack information; determining a potential threat factor of each device based on the potential propagation device of the next attack, the importance factor and the severity factor; determining an early warning level of each device in a next attack time range based on the potential threat factor of each device, and sending early warning information to a manager based on the early warning level; the accuracy of power grid safety early warning can be improved.

The invention discloses an echo cancellation method for equipment with AGC (Automatic Gain Control), which comprises the following steps: step 1, presetting a static reference parameter set of the AGC, taking the static reference parameter set as an initial value for dynamically adjusting parameters of the AGC, the static reference parameter set comprising target gain, attack time and release signal duration; 2, setting a triggering condition for triggering and adjusting AGC parameters based on the amplitude characteristics of the multi-channel audio stream monitored by the hardware interface of the equipment; and step 3, when the triggering condition is met, executing an adjustment strategy which is used for adjusting the parameters of the AGC so as to realize echo cancellation by adjusting the parameters of the AGC. According to the method and the device, the AGC parameters are dynamically adjusted, the two triggering conditions are adopted, and the corresponding adjustment strategies are executed, so that the echo can be better eliminated, and the initial echo and the process probability echo are effectively avoided or reduced.

The invention discloses a test method, a test device, electronic equipment and a computer program product, which are applied to the technical field of computer security, and the test method comprises the following steps: under the condition that a first thread occupies a target memory area, releasing a target pointer pointing to the target memory area, and after the first thread releases the target pointer, starting the target pointer to the target memory area; the target pointer is emptied; an interrupt storm is constructed, the opportunity of the first thread to empty the target pointer is delayed, and the interrupt storm is formed by interrupt between processors; in the look-ahead state, a second thread is used for simulating an attack behavior, a test result is generated, and the attack behavior comprises the behavior of reading the data in the target memory area. According to the method and the device, the opportunity of null target pointer of the first thread is delayed, so that longer time is reserved for a simulation attacker to implement a simulation attack behavior, and an inaccurate test result caused by the fact that a security hole cannot be exposed due to too short simulation attack time can be avoided to a certain extent.