46 results about "Jamming attack" patented technology

The invention discloses a satellite secure transmission optimization method and system based on joint anomaly detection, mainly solving the problem of low end-to-end transmission reliability under the condition of network attack in the prior art, and the implementation scheme comprises the following steps: constructing a time-varying network topology according to constellation configuration; periodically updating a network topology and a satellite neighbor node set according to the law of satellite orbital motion; the network is monitored in real time based on an anomaly detection mechanism, whether the current network is subjected to interference attack and DoS attack is judged in time, and whether the current satellite can safely transmit data is judged; and according to indexes such as node states, link hops, detection precision, node load capacity and link transmission delay, and according to a network topology and a neighbor node set at the current moment, determining a routing control optimization problem, and guiding each satellite to select an optimal transfer satellite along a transmission direction according to an optimal solution to obtain an end-to-end optimal transmission path. The method can actively trigger a detection mechanism to quickly identify abnormal nodes, obtains a safe and reliable end-to-end transmission path, and can be used for a low earth orbit satellite network.

A computer-implemented method (CIM), according to one embodiment, includes performing a detecting and monitoring adversarial jamming (MDJ) process for an edge environment that includes a first edge device and a central hub. In response to a determination that a jamming attack event is likely to occur, a pre-emptive edge user device protection process (PPP) is caused to be deployed. In response to a determination that a jamming attack event has occurred, a post-process jammed data (PJD) process is caused to be deployed at a recipient of a wireless transmission subject to the jamming attack event. The CIM further includes generating, based on results of deploying the PPP and / or the PJD process, a first set of new parameters for a model of a device that sent the wireless transmission, and causing the first set of new parameters to be distributed to the model of the device that sent the wireless transmission.

The present disclosure relates to a spectrum sharing method that can prevent jamming attacks and frequency interference through frequency hopping when operating multiple units simultaneously in a non-terrestrial network. The spectrum sharing method through frequency hopping according to an embodiment of the present disclosure is a spectrum sharing method through fast frequency hopping (FFH) in a plurality of cells assigned with different frequencies, the spectrum sharing method including: identifying occupied frequencies assigned to a cell at which a communication unit is positioned and at least one adjacent cell, respectively; and changing collision frequencies matching the occupied frequencies in a preset hopping pattern in the communication unit to a frequency that is not the occupied frequencies.

The invention discloses an intelligent resource allocation method for an unmanned aerial vehicle cluster communication network under interference attack, and belongs to the fields of unmanned aerial vehicle communication, unmanned aerial vehicle trajectory optimization, unmanned aerial vehicle resource allocation, interference resistance and the like. Path planning is carried out by using an improved simulated annealing algorithm, and spectrum allocation and power selection are optimized under various constraint conditions, so that the average transmission delay of the system is reduced, and the interference influence is reduced. In order to solve the problem that an optimal allocation strategy cannot be found in limited time, an optimization algorithm DDQNper-TL based on DDQN is provided according to a priority experience playback and transfer learning algorithm. Simulation results show that the performance of the method is obviously superior to that of reference algorithms such as non-optimized DDQN under the interference attack condition, and lower average transmission delay is achieved.

The application belongs to the technical field of communication, and discloses a wireless communication terminal anti-interference method and system; each terminal is allocated a terminal identification code before data communication after accessing a network, and a main channel and a backup channel resource pool are specified; each terminal perceives the state of each channel in real time, records the terminal identification code of other terminals in the environment, the channel used by each terminal and the channel suffering from interference attack each time data transmission; each terminal independently adopts a given Q-learning algorithm to model the behavior of an interferer, predict an interference channel and finally select a channel according to the above information; if the main channel will not suffer from interference, the main channel is selected for the next data transmission, otherwise, a cyclic channel allocation calculation is made according to the terminal identification code, the predicted interference channel and the backup channel resource pool. The application effectively realizes anti-interference in the scene of multiple terminals, has low calculation complexity, does not need information interaction between terminals and is easy to realize.

In a wireless communication system, at least one UE detects GNSS signal spoofing / jamming and reports a detected spoofing / jamming attack to a server in the network apparatuses using an extended LPP GNSS error reporting format with an additional error cause and an attack probability metric. Further, the network apparatuses may take an implementation-dependent decision depending on crowd-sourced information of one or more spoofing / jamming attack reports received from one or more UEs.

The application provides a dynamic address hopping attack target depth interference adjustment method and system, and belongs to the technical field of network security.The method comprises the following steps: searching for idle IP addresses of each network segment in a user network area through a network scanning tool; generating a large number of trapping hosts based on the collected idle IP addresses; performing same-side mixed deployment on the generated trapping hosts and real hosts of the user; determining the hopping range of the IP addresses of the trapping hosts, setting specific IP address segments according to network planning, setting the hopping port number range of each trapping host, and dividing different port groups according to the service type; through the deployment of the dynamic address hopping and the large number of trapping hosts, the difficulty of the attacker in identifying and attacking the real host is significantly improved, so that the attack behavior of the attacker is effectively interfered, and the overall network security is improved.

The application discloses a binomial sampling circuit applied to post-quantum cryptographic algorithm and resisting side channel attacks, comprising a random number generation unit, a binomial sampling unit and a control logic unit; the random number generation unit is used for generating pseudo random numbers according to input data; the pseudo random numbers comprise true data and false data; the binomial sampling unit is used for synchronously performing binomial sampling on the true data and the false data; and the control logic unit is used for controlling the random number generation unit and the binomial sampling unit to operate according to external instructions. The binomial sampling circuit applied to post-quantum cryptographic algorithm and resisting side channel attacks disclosed by the application increases the difficulty of analysis of attackers by generating pseudo random numbers, synchronously samples the true data and the false data to interfere with the attackers, and jointly realizes the protection against side channel attacks, thereby effectively improving the security of a Kyber cryptographic system and reducing the risk of being attacked by side channels.

The invention relates to a method for detecting and mitigating an interference attack by an interference transmitter in a wireless V2X communication network in which a plurality of mobile devices communicate with one another, comprising: analysing received signals with respect to power-related parameters, wherein an interference signal is detected in the event of a deviation from specified power parameters, classifying the interference signal according to whether the interference signal is a genuine interference signal or a false interference signal, wherein an energy pattern of the interference signal is determined on the basis of the estimated parameters, and wherein an AI-based discriminator is used such that after a test with an appropriate probability sequence either the interference signal is detected as a genuine interference signal or the interference signal is detected as a false interference signal, classifying the genuine interference signal for different radio interference attacks such that a mitigation measure of the genuine interference signal takes place, on the basis of the type of interference attack determined, in such a way that the effect of the interference transmitter is weakened. An autonomous vehicle equipped with mobile sensors, particularly drones, which can be operated in both coupled and autonomous modes, wherein said drones can be deployed with reconfigurable intelligent surfaces (RIS) for mitigating interference attacks and defending against cyber threats, such as interference transmitters, to ensure security and efficiency of the V2X wireless communication network.

The invention discloses a preemption and perception cross spoofing attack detection method based on systematic residual check. The method comprises the following steps: acquiring a damaged signal subjected to a PSCS attack; performing discrete Fourier transform on the damaged signal to obtain a plurality of resource elements, and extracting a phase gradient and an amplitude deviation for each resource element; defining a non-attack state constraint function and an attack state constraint function by using the phase gradient and the amplitude deviation corresponding to each resource element, so as to express the construction of test statistics as a minimum and maximum optimization problem; a minimum and maximum optimization problem is converted into a semi-definite programming problem through a kernel tensor completion technology, and test statistics are obtained by solving the semi-definite programming problem; based on the test statistics, calculating a detection threshold according to a false alarm probability; and calculating the current test statistic of the to-be-detected signal in the current time slot, and if the current test statistic is greater than the detection threshold, judging that the PSCS attack exists, thereby realizing the effective seizing and sensing cross spoofing attack detection method.

Provided are a method and a system for detecting position measurement anomalies in a global navigation satellite system (GNSS) for a plurality of stationary GNSS receivers. Therein, GNSS measurement indication from a GNSS receiver is determined to be affected by an anomaly if the GNSS measurement indication is not received at a configured timing, and / or if the measured GNSS signal parameter value is invalid and / or deviates from a recorded position of the GNSS receiver and / or or from a recorded GNSS signal parameter value from a past measurement by the stationary GNSS receiver. Accordingly, the present disclosure facilitates cost efficient, area-wide, high-resolution, and continuous monitoring of GNSS anomalies (such as spoofing and / or jamming attacks).

The present invention addresses the problem that satellite communication systems are susceptible to interference attacks due to open channels and relatively fixed satellite orbit information, and proposes a highly resilient anti-interference satellite communication method based on dual-beam user terminals and multiple satellites, which belongs to the field of satellite communications. During the operation of the main beam of the user terminal, the backup beam polls and detects the available communication resources of multiple satellites to obtain the channel status. When the main beam is interrupted by an interference attack, the backup beam is switched to the main beam in a very short time to restore and maintain smooth communication. The main beam is then switched to the backup beam simultaneously, and polling continues between the available communication resources, thereby forming a user satellite communication network with higher resilience and stronger anti-interference capabilities. The method of the present invention has a short anti-interference and communication maintenance time for the satellite communication system after interference, and is suitable for the design and development of key user satellite communication systems and user terminals with resilience and anti-interference communication requirements as the main requirements.

A short packet covert communication method for countering change-point detection-based interference attacks includes information sensing, key generation and codebook sharing, information encoding, information transmission, and decoding of the decrypted signal using a shared Gaussian codebook. The method includes a sending node, a receiving node, and a detection node. The detection node uses Shewhart change-point detection, meaning it makes a judgment each time it observes channel usage. Once the detection node detects a transmission from the sending node, it launches an interference attack to fully disrupt information transmission. Therefore, when a transmission is detected by the detection node and subjected to an interference attack, the destination node cannot successfully decode the data. To successfully transmit information, the sending node uses any moment during the interference gap to randomly transmit private data encoded with a finite block length with a priori transmission probability, thereby enhancing the concealment of the transmission.

The invention discloses an elastic multi-target monitoring and tracking method for resisting a composite attack, which comprises a layered framework of two layers, namely a communication layer and a decision layer, and is characterized in that in the first communication layer, a game theory method is provided based on a maximum and minimum distribution principle, and the composite attack is resisted through communication graph reconstruction; the monitoring elasticity and the tracking performance of the system under denial of service attack and sensor interference attack are obviously improved; and in a second decision layer, a distributed collision avoidance controller fusing a control obstacle function and a weighted Thiessen polygon graph is designed, target radiation attack can be effectively counteracted, and adaptive risk perception tracking is ensured while an obstacle avoidance function is realized. The method provided by the invention is suitable for a scene in which multiple robots monitor and track multiple targets in a dangerous environment, can maintain the monitoring and tracking capability of the scene, and realizes stable monitoring and efficient tracking in a complex confrontation environment.

The invention discloses a network space endogenous security protection system, method and device based on mimicry defense and a medium, and belongs to the technical field of network space security protection, and the method comprises the steps: carrying out attack perception and application layer dynamic cheating through a network layer intelligent threat hunting module; deep threat analysis and network layer intelligent hunting are carried out through the network layer intelligent threat hunting module; host layer anomaly detection and endogenous immune treatment are carried out through a host layer endogenous safe immune module; and unified scheduling and cross-layer collaborative response as well as quantitative evaluation and active closed-loop optimization are carried out through the unified scheduling and quantitative evaluation center. According to the invention, through dynamic traffic scheduling and behavior simulation trapping of the application layer mimicry camouflage module, attacker detection is effectively confused and interfered, and the active defense capability is improved; by means of a multi-engine fusion analysis and predictive AI model of a network layer intelligent threat hunting module, high-precision detection and attack chain reconstruction of known and unknown threats are realized.

The application discloses a method for resisting satellite Internet of Things uplink interference attack, and a satellite Internet of Things system comprises a central gateway, a plurality of service areas and a space segment; the service area comprises a plurality of legal terminal nodes, and the space segment is composed of one or more communication satellites in geostationary or non-geostationary orbits. Each communication satellite provides a single or multiple beams to cover different service areas, the satellite can connect the service areas to the central gateway, and then store collected messages and transmit the messages to the central gateway. The method comprises the following steps: calculating a MAC layer load G, calculating a preamble time, calculating an average data packet arrival number, and calculating a minimum IC step length under a specified detection probability through a Poisson distribution. The application has the advantages that the system performance decline caused by the preamble camouflage attack can be resisted, the preamble deception interference which has a great influence on the system performance is effectively eliminated, and the system stability is greatly improved.

The present disclosure relates to a technique for configuring secured (or hidden) Physical Random Access Channel (PRACH) resources for trusted User Equipments (UEs) in a wireless communication network. According to the technique, a set of secured PRACH resources each having an ID is signaled by a network node to a trusted UE (preferably by using an encrypted message). When it is detected that a set of public PRACH resources currently used by the trusted UE for PRACH preamble transmissions is under a malicious attack (e.g., a jamming attack), the network node selects, among the set of secured PRACH resources, one or more secured PRACH resources which may be used instead of the public PRACH resources for the PRACH preamble transmissions. The ID(s) of the selected secured PRACH resource(s) is(are) signaled by the network node to the UE. The PRACH resources thus configured are better protected from malicious attacks.

The invention discloses a reactive interference-oriented secure cognitive radio network power allocation method, and belongs to the field of communication resource allocation and anti-interference secure communication of a cognitive radio network. The implementation method comprises the following steps: analyzing secondary user communication requirements and disturber behavior characteristics, constructing a CR network model containing time-varying channel gain and a random reactive interference model, and deducing an optimal dynamic energy detection threshold of a disturber; constructing a CR network power distribution optimization problem by taking maximization of a secondary user communication rate and avoiding of reactive interference attacks as targets; aiming at the dynamic uncertainty of channel gain and interference behaviors, constructing a Markov decision process based on a deep reinforcement learning framework, and giving definitions of basic elements such as states, actions, rewards and the like; and constructing a double-depth Q network, and solving to obtain a CR network power distribution scheme, thereby realizing the power distribution of the CR network in the reactive interference scene. The method has the advantages of high communication security, high robustness in a complex environment and the like.

In one example embodiment, a method for detecting signals intended to interfere with satellite signaling includes receiving, by a receiving node, a signal masquerading as a satellite signal from a signal source, determining an estimated location of the receiving node based on the orbital position of the satellite and characteristics of the signal, comparing the estimated location of the receiving node to a reference location of the receiving node, determining that the signal source is a spoofing source other than a satellite, and determining a location of the spoofing source based in part on the estimated location.

The invention relates to a system for detecting and / or defusing an interference attack by a jammer in a wireless communication network in which a plurality of mobile users are located, comprising a signal detection unit for detecting signals in the communication network, a monitoring unit for monitoring a radio channel with a signal coding estimation module for estimating a signal coding of the jammer and / or a signal power estimation module for estimating a signal power of the jammer and / or a position estimation module for estimating a position of the jammer and / or a signal coding profile of the jammer, an evaluation unit for generating an interference attack detection signal via the interference attack object depending on a result of the signal coding estimation module and / or the signal power estimation module and / or the position estimation module.

The invention provides an attack target depth interference adjustment method and system based on dynamic address hopping. Belongs to the technical field of network security. The method comprises the following steps: in a user network area, searching an idle IP address of each network segment through a network scanning tool; generating massive trapping hosts by taking the collected idle IP addresses as a reference; carrying out same-side mixed deployment on the generated trapping host and the real host of the user; determining a jump range of an IP address of a trapping host, and setting a specific IP address field according to network planning; setting a jumping port number range for each trapping host, and dividing different port groups according to service types; through the deployment of dynamic address hopping and massive trapping hosts, the difficulty of identifying and attacking a real host by an attacker is remarkably improved, so that the attack behavior of the attacker is effectively interfered, and the overall security of the network is improved.

The invention provides a V2V resource allocation method based on a D3QN-LSTM under interference attack, which comprises an anti-interference resource allocation strategy based on the D3QN-LSTM, and is characterized in that random interference, sweep frequency interference and sensing interference are resisted through an adaptive defense mechanism comprising strategic channel switching and dynamic power adjustment; an anti-interference resource allocation problem is converted into an MADRL framework to process PUs access, the influence of malicious interference attack on a channel and the non-stationary characteristic of cognitive Internet of Vehicles, and joint optimization of transmission power allocation and channel access decision is performed through a V2V intelligent agent based on a D3QN-LSTM algorithm architecture. LSTM is integrated into a feature layer so that a vehicle can accurately estimate the system state and extract global information, each pair of V2V links learns an optimal strategy through interaction with the environment through an intelligent agent, and rewards related to PUs, malicious interference channels and the V2V link outage probability are combined through a reward function mechanism; according to the method, the data transmission success rate of the V2V link is optimized, and the communication stability and reliability of the V2V link can be guaranteed under malicious interference attacks.

The invention provides a flight ad hoc network airspace anti-interference method based on channel alternating estimation. The quality of wireless communication is limited by a complex environment, a fading effect of a wireless channel, openness and the like, so that a flying ad hoc network system is more easily interfered and attacked. In order to solve the problem, an MIMO-OFDM spatial filtering method based on channel alternating estimation is discussed to be used for resisting strong continuous interference attacks. According to the method, under the interference attack, the required signal can be effectively recovered based on the spatial domain filtering basic principle through the alternative iterative estimation of the sender channel and the interference channel. Simulation results show that the method has excellent anti-interference performance, bit error rate can be greatly reduced under strong interference attack, and transmission reliability is guaranteed.

The invention discloses a virtual digital outbound intelligent customer service system based on generative AI, relates to the technical field of virtual customer service management, and solves the technical problems that the system lacks an effective monitoring mechanism for self service quality and has a single encryption processing mode for interactive data. According to the method, the overall state of the intelligent customer service is monitored in real time by calculating multi-dimensional indexes such as the knowledge anchor-free answer rate, the semantic ambiguity answer proportion and the high-frequency complaint question association rate, management personnel can conveniently optimize a knowledge base, an answer template or a service process in a targeted mode, the user service experience and the system reliability are improved, and the user experience is improved. A random modification feature is generated according to the byte size of a data packet, the data packet is dynamically bundled and sent out of order, and a random delay transmission strategy is introduced, so that analysis of an attacker on traffic features is effectively interfered, data eavesdropping and content tampering are prevented, and the security and privacy of user interaction information in the transmission process are guaranteed.

A method for anti-jamming communication of UAV edge computing based on reinforcement learning, which involves fields such as UAV communication, UAV path planning, edge computing, anti-jamming communication, etc. It fully exploits key information such as the UAV's position, remaining battery power, and communication rate, combines parameters such as the communication channel state and communication performance between the UAV and ground devices and jammers, and proposes an intelligent resource management and control scheme based on deep reinforcement learning to dynamically optimize the UAV's trajectory and the user's transmission power, effectively resisting malicious jammer attacks while completing mobile edge computing tasks. In a complex malicious jamming attack environment, it still efficiently improves the UAV's communication rate and ensures the throughput performance of edge computing tasks.

The present disclosure provides an apparatus and method for detecting and responding to radio frequency jamming attacks in an Open RAN environment. An O-DU generates physical layer data including SNR, CQI, BLER, or MCS and transmits the data to a Near-RT RIC through an E2 interface. The Near-RT RIC stores the physical layer data in an SDL. An RF jamming detection xApp receives the physical layer data from the SDL to detect radio frequency jamming attacks. The xApp transmits the detected attack information to a network slice management rApp of a Non-RT RIC through an O1 interface to enable dynamic response through network slicing.

A solution for radio jamming detection is disclosed. The solution comprises determining M subcarriers in a time-frequency resource grid to be blanked and outputting the M subcarriers in the time-frequency resource grid to be blanked by performing at least one of the following operations: first determination of a number M of subcarriers in a time-frequency resource grid to be blanked based on probability of detecting a jammer attack or on channel quality of subcarriers in the time-frequency resource grid, second determination of which M subcarriers in the time-frequency resource grid are blanked taking into account the channel quality of subcarriers in the time-frequency resource grid.

In an ultra-wideband (UWB) communication network, a controller anchor changes which anchor of a group of anchors serves as initiator for each of multiple ranging rounds. Based on the capabilities of the anchors in the UWB communication network, the controller selects among multiple modes for designating which anchor serves as initiator for each ranging round. In a first mode, the anchors take turns serving as the initiator for successive ranging rounds in round robin fashion. In a second mode, the anchors randomly take turns serving as the initiator for ranging rounds. By dynamically selecting an initiator for each ranging round, launching a successful jamming attack becomes significantly more complicated.

The application provides a hidden trailing jamming attack detection method based on geometric consistency and constraint screening, which is suitable for a UAV-assisted mobile edge computing system. The method comprises the following steps: acquiring the receiving signals of each time slot legal UAV, calculating the time slot logarithmic power statistics and combining the map anchor residual to generate a detection residual; screening an attack state set that meets the physical feasibility condition and the service damage condition from the constructed attack set, and determining the authentication minimum offset on the set to construct the robust log-likelihood ratio increment of each time slot in combination with the detection residual; based on the increment, the sequential accumulation is carried out to obtain the cumulative statistics; when the statistics exceed the preset detection threshold, it is determined that the control link is subjected to trailing jamming. Through the combination of geometric consistency, physical constraint screening and worst-case authentication, the reactive navigation trailing jamming can be effectively detected, and the continuity and reliability of the control link can be ensured under the condition that the false alarm is controllable.

This invention proposes an intent-driven system game-theoretic anti-interference method, solving the problem of network node interference detection and defense in wireless communication networks. The implementation includes: real-time sensing and storage of data from a network data monitoring model; constructing and utilizing an interference intent recognition model to determine the type of interference attack; constructing and utilizing an anti-interference game model based on incomplete information dynamic game theory to derive corresponding anti-interference strategies for three types of interference attacks; and deploying and implementing the anti-interference strategies. This invention introduces the concept of interference intent recognition into the anti-interference scenario of wireless communication networks and constructs an anti-interference game model based on incomplete information dynamic game theory, improving the anti-interference efficiency of network nodes under closed-loop management. This invention provides more and more accurate interference intent recognition types, more timely anti-interference decisions, and higher efficiency for use in wireless communication networks.