32results about How to "Improve defense efficiency" patented technology

The invention discloses a method and a system for monitoring DDOS (distributed denial of service) attacks in small flow, solves the problems that the existing DDOS attack detection technology is high in cost, complex to implement and high in misjudgment rate, cannot respond to DDOS attacks aiming at an application layer and the like, and provides the monitoring scheme of an integrated DPI (dots per inch) technology. A baseline analysis, component analysis and similarity analysis method is used to establish a normal use model, characteristics are accurately matched to detect the attacks in small flow and the application layer attacks, deployment at one point of an operator network and complete coverage of the operator network are achieved, and detection accuracy is increased.

The invention discloses a network attacker behavior analyzing method based on an attack graph. The method comprises the steps of establishing a network attacker behavior analyzing model and attracting attacks of attackers; carrying out comprehensive capturing on attack data through a data capturing mechanism; and generating an attack state transfer graph through combination of a finite-state machine and analyzing behaviors of the attackers according to possibility indexes of attack behaviors, skill level indexes of the attackers and destination indexes of the attackers. According to the network attacker behavior analyzing method based on the attack graph provided by the invention, the good foundation can be laid for design of an active defense system, the network attacks can be defended, the attacks can be prevented before the network attacks occur, one part of the attacks are screened, a cybercrime can be effectively prevented, the defense efficiency is improved, and the defense cost is reduced.

The invention provides a defensive system and method of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle countering. The defensive system of the unmanned aerial vehicle comprises a ground detection subsystem, a command and control subsystem and a disposition subsystem. The ground detection subsystem is used for detecting and tracking the target unmanned aerial vehicle and sending position information of the target unmanned aerial vehicle to the command and control subsystem; the command and control subsystem is used for receiving the position information and a capturing instruction input by a commander according to the position information and sending the capturing instruction to the disposition subsystem; the disposition subsystem comprises a capturing unmanned aerial vehicle, an unmanned aerial vehicle ground station and an RTK navigation system, and is used for receiving the position information and the capturing instruction, and the capturing unmanned aerial vehicle is guided to capture the target unmanned aerial vehicle through the RTK navigation system. With the defensive system and method of the unmanned aerial vehicle, high-precisionnavigation information can be obtained, the target unmanned aerial vehicle is convenient to capture, and the defensive efficiency of the unmanned aerial vehicle is improved.

The present invention provides a data safety defense system and method based on a cloud terminal, and a cloud terminal safety system. The data safety defense system comprises a network monitoring management module which is used for monitoring the network condition of the cloud terminal, limiting the access of the cloud terminal, starting a negative-transfer module, and guiding a current access data packet to the negative-transfer module, the negative-transfer module which is used for intercepting the current access data packet, sending the legitimate access data packet in the intercepted current access data packet to a positive-transfer module, and the positive-transfer module which is used for receiving and storing the legitimate access data packet. Since the network condition of the cloud terminal is monitored in real time, when the cloud terminal is attacked, the access data packet is timely intercepted, the operation of a router is controlled, and the unlawful attack to the cloud terminal is effectively prevented.

The invention discloses a web intelligent defense method, which comprises the steps of: determining whether features of a request are recorded in a data sheet in which attack information is recorded when receiving the request sent by a client; if so, determining whether a number of attacks of the request within preset first duration exceeds a preset threshold; and executing a preset defense rule when the number of attacks of the request within the preset first duration exceeds the preset threshold. The web intelligent defense method avoids the process of comparing each request with an attack feature library repeatedly, thereby reducing workload, improving the defense efficiency, and correspondingly improving the normal service quality in the network and the performance of the entire network. Correspondingly, a web intelligent defense device, web intelligent defense equipment and a readable storage medium disclosed by the invention further have the above technical effects.

The embodiment of the invention discloses a vulnerability scanning and repairing system and method based on Oval, and the system includes an Oval knowledge base, an Oval parsing module, a vulnerability scanning module, and a vulnerability repairing module. The Oval knowledge base, the vulnerability scanning module and the vulnerability repairing module are connected to the a vulnerability parsingmodule, wherein, the Oval knowledge base is used for storing vulnerability definition, vulnerability scanning definition and vulnerability repairing definition; the vulnerability scanning module is used to scan the vulnerability of the tested object. The vulnerability repair module is used to repair the scanned vulnerabilities. The vulnerability parsing module is used to send vulnerability definitions and vulnerability scanning definitions to the vulnerability scanning module and to send vulnerability repair definitions to the vulnerability repair module according to the vulnerability. The invention can pre-repair the leak in an active state before the leak occurs, and the leak prevention efficiency is improved.

The invention discloses an image recognition backdoor defense method and device based on swarm intelligence, and a medium. The method comprises the following steps: selecting neural network models with dense connection as seed neural network models based on the incidence relation of a plurality of neural network image recognition models in a distributed cluster and according to the ranking of connection density; aiming at every two seed neural network models, performing distillation operation on the two seed neural network models by utilizing attention distillation representation, and extracting an attention activation graph Al which is invalid to the back door attack of the seed neural network models; and measuring the Euclidean distance and the cosine distance of activation attention maps Al of the two seed neural network models by designing a robust distillation loss function L, allowing the seed neural network models to calculate gradient values based on the L and to carry out back propagation, and updating the parameters of the seed neural network models. The performance and efficiency of an image recognition back door defense algorithm based on swarm intelligent under the image recognition back door defense task reach a current optimal level.

The invention relates to the field of climate monitoring and early warning, in particular to a weather forecast and early warning service system, which comprises a weather monitoring point, an internet of things, a weather monitoring center and a forecast and early warning service point, wherein the weather monitoring point is connected with the weather monitoring center through the internet of things. The weather monitoring center is connected with a mobile device I and the forecast and early warning service point through the communication network. The system effectively solves the problems that the emergency processing efficiency is low and the life and property loss is increased due to the fact that the natural disaster forecasting and early warning service for sudden and turning weather changes is not in time, can effectively prevent and early warn, improves the emergency processing efficiency, and is high in practicability. Life and property loss caused by the situation is avoidedor reduced to the maximum extent, life and property safety is protected, and healthy and orderly development of social economy in our district is promoted.

The invention discloses a dynamic defense system for resisting large-flow attacks in a honey farm system. The system comprises an attack decoy module arranged at a subnet gateway, an attack element extraction module arranged at the center of a honey farm and in communication connection with the attack decoy module, an attack element training module arranged at the center of the honey farm and connected with the attack element extraction module, a defense strategy making module arranged in the center of the honey farm and connected with the attack element extraction module and the attack element training module, a dynamic data feedback module arranged in the center of the honey farm and connected with the attack decoy module and the defense strategy making module, and a large-flow attack defense module arranged in the center of the honey farm and is connected with the defense strategy making module and the attack decoy module. According to the dynamic defense system for resisting the large-flow attack in the honey farm system, the network security defense performance and security of the honey farm system in response to the large-flow attack are effectively improved.

The invention discloses a virus defense optimization method and device, a storage medium and computer equipment, relates to the technical field of network security, and mainly aims to solve the problem that a targeted searching and killing tool is written only after virus features are stored in a virus library in existing computer virus defense, the defense requirement of the novel computer viruscannot be quickly met, and the defense of the computer system fails. The method comprises the steps of judging whether feature information in a target file is matched with defense feature informationin a preset defense feature library or not, and determining the defense feature information in the preset defense feature library according to expected searching and killing and/or repairing of suspicious files under different defense scenes; and if the feature information is matched with the defense feature information, calling a defense operation bound with the defense feature information, and executing the defense operation. The invention is mainly used for optimizing virus defense.

The invention provides a vulnerability defense method and system, and the method comprises the steps: carrying out the independent flow monitoring and business volume monitoring of each pre-divided business module based on a pre-constructed neural network model, predicting the future business volume of each business module, and obtaining the predicted business volume corresponding to each business module; when monitoring that the traffic of any business module is abnormal and/or the business volume is higher or lower than the predicted business volume, detecting whether the business module is attacked; and if the attack is detected, determining an attack type, and executing a defense strategy and a counterattack strategy according to the attack type. According to the scheme, the business modules are divided, the neural network model obtained through pre-training is used for carrying out independent flow monitoring and business volume monitoring on each business module, when any business module is attacked, attacks are defended in time, so that the security risk is reduced, and the attacks are defended in a targeted mode according to the attack types. The defense efficiency is improved, and the overall safety level is improved.