21 results about "Jamming attack" patented technology

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 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 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.

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 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 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.

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.

The application discloses a virtual digital outbound intelligent customer service system based on generative AI, and relates to the technical field of virtual customer service management.The application solves the technical problems of lack of effective monitoring mechanism for service quality and single encryption processing mode for interactive data.The application monitors the overall state of the intelligent customer service in real time through the calculation of multi-dimensional indexes such as the knowledge anchor point answer rate, semantic ambiguity answer proportion and high-frequency complaint problem correlation rate, so as to facilitate the targeted optimization of the knowledge base, answer template or service process by the management personnel, improve the user service experience and system reliability, generate random modification features for the data packet byte size, dynamically bundle data packets and send them in random order, introduce a random delay transmission strategy, effectively interfere with the analysis of the traffic characteristics by attackers, prevent data eavesdropping and content tampering, and guarantee the safety and privacy of the user interactive information in the transmission process.

The method of the present invention relates to utilizing the convergence patterns of sparse coding for detecting primary user emulation / signal jamming attacks in cognitive radio settings. The method basically comprises a training phase and a testing phase. The method can distinguish between the following hypotheses: H0, which indicates that there is no primary user, only noise; H1, which indicates that there is a legitimate primary user with the right to use the spectrum and that secondary users should not use the spectrum; and H2, which indicates that there is a primary user emulator / signal jammer in the environment.

The invention discloses an anti-interference and sensing integrated system and an optimization method. The system comprises a base station BS, an RIS, a jammer, a communication user and a sensing target. According to the optimization method, a base station transmitting beam forming vector, a receiving filter and a phase shift matrix of a reconfigurable intelligent surface are designed through joint optimization, and the sum of the weighted communication rate and the radar signal interference-to-noise ratio is maximized under the condition that interference attacks exist. In order to solve the non-convex optimization problem, an iterative algorithm is adopted, a main minimization and successive convex approximation technology is combined, and a closed-form solution of a receiving filter, a semi-definite programming relaxation solution of transmitting beam forming and a convex approximation subproblem sequence solution of surface phase shifting are given respectively. Simulation results show that the scheme provided by the invention can effectively suppress interference and significantly improve the communication rate and radar sensing performance of the system.

The invention relates to a method for detecting and mitigating jamming attacks in a wireless V2X communication network in which several mobile devices communicate with each other, comprising: analyzing received signals with respect to power-related parameters, wherein a jamming signal is detected if there is a deviation from predetermined power parameters; classifying the jamming signal according to whether the jamming signal is a true jamming signal or a spurious jamming signal, wherein an energy pattern of the jamming signal is determined based on the estimated parameters and wherein an AI-based discriminator is used so that, after a test with an appropriate probability sequence, either the jamming signal is recognized as a true jamming signal or the jamming signal is recognized as a spurious jamming signal; classifying the true jamming signal according to different radio jamming attacks.so that, depending on the detected type of jamming attack, a mitigation measure is taken against the actual jamming signal, such that the effect of the jammer is weakened. An autonomous vehicle equipped with mobile sensors, in particular drones, which can operate in both coupled and autonomous modes, wherein these drones can be used with reconfigurable intelligent surfaces (RIS) for mitigating jamming attacks and defending against cyber threats such as jammers, in order to ensure the security and efficiency of the wireless V2X communication network.

The invention discloses an unmanned aerial vehicle-oriented sweep frequency interference attack defense method, and aims to construct a full-chain defense architecture integrating detection, suppression and traceability. According to the method, firstly, based on signal features and frequency spectrum changes, rapid detection and type identification of frequency sweeping, broadband and burst interference are achieved; then, by means of instantaneous frequency estimation and the self-adaptive notch filtering technology, interference signals are suppressed while the communication stability is kept, and real-time protection of signal integrity is achieved; and finally, performing dynamic estimation and traceability on the position of an interference source in combination with a signal strength measurement and uncertainty constraint positioning algorithm, thereby realizing detection-suppression-traceability closed-loop defense on the sweep frequency interference attack in a complex electromagnetic environment. The method is clear in structure and rapid in response, has high detection precision, suppression robustness and traceability positioning capability, and can be widely applied to unmanned aerial vehicle task safety control and anti-interference system design.

A method for wireless communication at a victim user equipment (UE) includes receiving a configuration, from a network, of carrier wave cross link interference measurement resources for detecting carrier wave cross link interference originating from a forward link of an aggressor UE. The aggressor UE transmits the forward link to an internet of things (IoT) device. The method also includes measuring the carrier wave cross link interference on the measurement resources. The method further includes transmitting a carrier wave cross link interference report in response to satisfying a condition with respect to downlink reception at the victim UE.

The present application relates to a kind of physical layer interference attack recovery methods for software-defined optical network, belong to optical fiber communication security technical field, including the following steps: S1: define macroscopic optical network physical layer signal interference attack recovery framework;S2: build in-band, out-of-band interference attack implementation 16QAM dual polarization wavelength division multiplexing coherent communication system;S3: construct and train the end-to-end attack recovery model based on machine learning;S4: define mild, intensity in-band interference attack;S5: define mild, intensity out-of-band interference attack;S6: by the end-to-end attack recovery model based on machine learning of well-trained different attack intensity, different attack type interference attack recovery is realized.The present application realizes the recovery of attack without additional optical path resources and high recovery rate.