Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelato...Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelator outputs.However,the accuracy of the delay estimation is limited by the spacing of the correlators.To address this,an innovative anti-spoofing method is introduced,which incorporates distinct coarse and refined stages for more accurate spoofing estimation.By leveraging the coarse delay estimates obtained through maximum likelihood estimation,the proposed method establishes the Windowed Sum of the Relative Delay(WSRD)statistics to detect the presence of spoofing signals.The iterative strategy is then employed to enhance the precision of the delay estimation.To further adapt to variations in the observation noise caused by spoofing intrusions and restore precise position,velocity,and timing solutions,an adaptive extended Kalman filter is proposed.This comprehensive framework offers detection,mitigation,and recovery against spoofing attacks.Experimental validation using datasets from the Texas Spoofing Test Battery(TEXBAT)demonstrates the effectiveness of the proposed anti-spoofing method.With 41 correlators,the method achieves a detection rate exceeding 90%at a false alarm rate of 10-5,with position or time errors below 15 m.Notably,this refined anti-spoofing approach shows robust detection and mitigation capabilities,requiring only a single antenna without the need for additional external sensors.These advancements can significantly contribute to the development of GNSS anti-spoofing measures.展开更多
With the widespread application of global navigation satellite system(GNSS),spoofing attacks pose a threat to the security and reliability of GNSS.It is of great significance to design effective GNSS spoofing detectio...With the widespread application of global navigation satellite system(GNSS),spoofing attacks pose a threat to the security and reliability of GNSS.It is of great significance to design effective GNSS spoofing detection technology to ensure the security and reliability of GNSS system applications for receiver users.Traditional spoofing detection techniques generally only determine whether a spoofing attack has occurred by monitoring the feature changes of one or two data information in the receiver.However,some spoofing modes can cleverly make the monitored data very close to the real data,thus avoiding these detection methods and easily making them ineffective.In this study,a GNSS spoofing jamming detection method based on hybrid kernel relevance vector machine(RVM)is proposed.The improved signal quality monitoring(SQM)movement variance,carrier noise ratio movement variance,pseudo range Doppler consistency,pseudorange residual,Doppler frequency,clock offset and clock drift are used as detection characteristics.This technology can detect GNSS spoofing signals,effectively improving the safety and reliability of GNSS systems.The experimental results show that this technology has high detection accuracy and anti-interference ability and can effectively respond to various forms of spoofing attacks.展开更多
Kubernetes has become the dominant container orchestration platform,withwidespread adoption across industries.However,its default pod-to-pod communicationmechanism introduces security vulnerabilities,particularly IP s...Kubernetes has become the dominant container orchestration platform,withwidespread adoption across industries.However,its default pod-to-pod communicationmechanism introduces security vulnerabilities,particularly IP spoofing attacks.Attackers can exploit this weakness to impersonate legitimate pods,enabling unauthorized access,lateral movement,and large-scale Distributed Denial of Service(DDoS)attacks.Existing security mechanisms such as network policies and intrusion detection systems introduce latency and performance overhead,making them less effective in dynamic Kubernetes environments.This research presents PodCA,an eBPF-based security framework designed to detect and prevent IP spoofing in real time while minimizing performance impact.PodCA integrates with Kubernetes’Container Network Interface(CNI)and uses eBPF to monitor and validate packet metadata at the kernel level.It maintains a container network mapping table that tracks pod IP assignments,validates packet legitimacy before forwarding,and ensures network integrity.If an attack is detected,PodCA automatically blocks spoofed packets and,in cases of repeated attempts,terminates compromised pods to prevent further exploitation.Experimental evaluation on an AWS Kubernetes cluster demonstrates that PodCA detects and prevents spoofed packets with 100%accuracy.Additionally,resource consumption analysis reveals minimal overhead,with a CPU increase of only 2–3%per node and memory usage rising by 40–60 MB.These results highlight the effectiveness of eBPF in securing Kubernetes environments with low overhead,making it a scalable and efficient security solution for containerized applications.展开更多
Unmanned aerial vehicle(UAV)swarm network consisting of a collection of micro UAVs can be used for many applications.It is well established that packet routing is a fundamental problem to achieve UAV collaboration.How...Unmanned aerial vehicle(UAV)swarm network consisting of a collection of micro UAVs can be used for many applications.It is well established that packet routing is a fundamental problem to achieve UAV collaboration.However,the highly dynamic nature of UAVs,frequently changing network topologies and security issues,poses significant challenges to packet forwarding in UAV networks.The existing topology-based routing protocols are not well suited in UAV network due to their high controlling overhead or excessive end-to-end delay.Geographic routing is regarded as a promising solution,as it only requires local information.In order to enhance the accuracy and security of geographic routing in highly dynamic UAV network,in this paper,we propose a new predictive geographic(PGeo)routing strategy with location verification.First,a detection mechanism is adopted to recognize malicious UAVs falsifying their location.Then,an accurate average service time of a packet in the medium access control(MAC)layer is derived to assist location prediction.The proposed delay model can provide a theoretical basis for future work,and our simulation results reveal that PGeo outstrips the existing geographic routing protocols in terms of packet delivery ratio in the presence of location spoofing behavior.展开更多
The Global Positioning System(GPS)plays an indispensable role in the control of Unmanned Aerial Vehicle(UAV).However,the civilian GPS signals,transmitted over the air without any encryption,are vulnerable to spoofing ...The Global Positioning System(GPS)plays an indispensable role in the control of Unmanned Aerial Vehicle(UAV).However,the civilian GPS signals,transmitted over the air without any encryption,are vulnerable to spoofing attacks,which further guides the UAV on deviated positions or trajectories.To counter the GPS,,m spoofing on UAV system and to detect the position/trajectory anomaly in real time,a motion state vector based stack long short-term memory trajectory prediction scheme is firstly proposed,leveraging the temporal and spatial features of UAV kinematics.Based on the predicted results,an ensemble voting-based trajectory anomaly detection scheme is proposed to detect the position anomalies in real time with the information of motion state sequences.The proposed prediction-based trajectory anomaly detection scheme outperforms the existing offline detection schemes designed for fixed trajectories.Software In The Loop(SITL)based online prediction and online anomaly detection are demonstrated with random 3D flight trajectories.Results show that the coefficient of determination(R^(2))and Root Mean Square Error(RMSE)of the prediction scheme can reach 0.996 and 3.467,respectively.The accuracy,recall,and F1-score of the proposed anomaly detection scheme can reach 0.984,0.988,and 0.983,respectively,which outperform deep ensemble learning,LSTM-based classifier,machine learning classifier and GA-XGBoost based schemes.Moreover,results show that compared with LSTM-based classifier,the average duration(from the moment starting an attack to the moment the attack being detected)and distance of the proposed scheme are reduced by 24.4%and 19.5%,respectively.展开更多
A triple-band miniaturized end-fire antenna based on the odd modes of spoof surface plasmonic polariton(SSPP)waveguide resonator is proposed in this paper.To meet the ever increasing demand for more communication chan...A triple-band miniaturized end-fire antenna based on the odd modes of spoof surface plasmonic polariton(SSPP)waveguide resonator is proposed in this paper.To meet the ever increasing demand for more communication channels and less antenna sizes,multi-band antennas are currently under intensive investigation.By a novel feeding method,three odd modes are excited on an SSPP waveguide resonator,which performs as an end-fire antenna operating at three bands,7.15-7.26 GHz,11.6-12.2 GHz and 13.5-13.64 GHz.It exhibits reasonably high and stable maximum gains of 5.26 dBi,7.97 dBi and 10.1 dBi and maximum efficiencies of 64%,92%and 98%at the three bands,respectively.Moreover,in the second band,the main beam angle shows a frequency dependence with a total scanning angle of 19°.The miniaturized triple-band antenna has a great potential in wireless communication systems,satellite communication and radar systems.展开更多
In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the ...In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the GNSS spoofing is proposed.First,a Hammerstein model is applied to model the spoofer/GNSS transmitter and the wireless channel.Then,a novel method based on the uncultivated wolf pack algorithm（UWPA） is proposed to estimate the model parameters.Taking the estimated model parameters as a feature vector,the identification of the spoofing is realized by comparing the Euclidean distance between the feature vectors.Simulations verify the effectiveness and the robustness of the proposed method.The results show that,compared with the other identification algorithms,such as least square（LS）,the iterative method and the bat-inspired algorithm（BA）,although the UWPA has a little more time-eomplexity than the LS and the BA algorithm,it has better estimation precision of the model parameters and higher identification rate of the GNSS spoofing,even for relative low signal-to-noise ratios.展开更多
The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation ...The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.展开更多
Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation...Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.展开更多
The BeiDou-Ⅱcivil navigation message(BDⅡ-CNAV)is transmitted in an open environment and no information integrity protection measures are provided.Hence,the BDⅡ-CNAV faces the threat of spoofing attacks,which can le...The BeiDou-Ⅱcivil navigation message(BDⅡ-CNAV)is transmitted in an open environment and no information integrity protection measures are provided.Hence,the BDⅡ-CNAV faces the threat of spoofing attacks,which can lead to wrong location reports and time indication.In order to deal with this threat,we proposed a scheme of anti-spoofing for BDⅡ-CNAV based on integrated information authentication.This scheme generates two type authentication information,one is authentication code information(ACI),which is applied to confirm the authenticity and reliability of satellite time information,and the other is signature information,which is used to authenticate the integrity of satellite location information and other information.Both authentication information is designed to embed into the reserved bits in BDⅡ-CNAV without changing the frame structure.In order to avoid authentication failure caused by public key error or key error,the key or public key prompt information(KPKPI)are designed to remind the receiver to update both keys in time.Experimental results indicate that the scheme can successfully detect spoofing attacks,and the authentication delay is less than 1%of the transmission delay,which meets the requirements of BDⅡ-CNAV information authentication.展开更多
This paper presents a new approach to estimate the true position of an unmanned aerial vehicle （UAV） in the conditions of spoofing attacks on global positioning system （GPS） receivers. This approach consists of tw...This paper presents a new approach to estimate the true position of an unmanned aerial vehicle （UAV） in the conditions of spoofing attacks on global positioning system （GPS） receivers. This approach consists of two phases, the spoofing detection phase which is accomplished by hypothesis test and the trajectory estimation phase which is carried out by applying the adapted particle filters to the integrated inertial navigation system （INS） and GPS. Due to nonlinearity and unfavorable impacts of spoofing signals on GPS receivers, deviation in position calculation is modeled as a cumulative uniform error. This paper also presents a procedure of applying adapted particle swarm optimization filter （PSOF） to the INS/GPS integration system as an estimator to compensate spoofing attacks. Due to memory based nature of PSOF and benefits of each particle＇s experiences, application of PSOF algorithm in the INS/GPS integ- ration system leads to more precise positioning compared with general particle filter （PF） and adaptive unscented particle filer （AUPF） in the GPS spoofing attack scenarios. Simulation results show that the adapted PSOF algorithm is more reliable and accurate in estim- ating the true position of UAV in the condition of spoofing attacks. The validation of the proposed method is done by root mean square error （RMSE） test.展开更多
The Global Positioning System(GPS)has become a foundation for most location-based services and navigation systems,such as autonomous vehicles,drones,ships,and wearable devices.However,it is a challenge to verify if th...The Global Positioning System(GPS)has become a foundation for most location-based services and navigation systems,such as autonomous vehicles,drones,ships,and wearable devices.However,it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools.Pervasive tools,such as Fake GPS,Lockito,and software-defined radio,enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected.Furthermore,it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors.To this end,we propose DeepPOSE,a deep learning model,to address the noise introduced in sensor readings and detect GPS spoofing attacks on mobile platforms.Our design uses a convolutional and recurrent neural network to reduce the noise,to recover a vehicle's real-time trajectory from multiple sensor inputs.We further propose a novel scheme to map the constructed trajectory from sensor readings onto the Google map,to smartly eliminate the accumulation of errors on the trajectory estimation.The reconstructed trajectory from sensors is then used to detect the GPS spoofing attack.Compared with the existing method,the proposed approach demonstrates a significantly higher degree of accuracy for detecting GPS spoofing attacks.展开更多
We investigate the guiding modes of spoof surface plasmon polaritons （SPPs） on a symmetric ultra-thin plasmonic structure. From the analysis, we deduce the operating frequency region of the single-mode propagation. ...We investigate the guiding modes of spoof surface plasmon polaritons （SPPs） on a symmetric ultra-thin plasmonic structure. From the analysis, we deduce the operating frequency region of the single-mode propagation. Based on this property, a spoof SPPs lowpass filter is then constituted in the microwave frequency. By introducing a transmission zero at the lower frequency band using a pair of stepped-impedance stubs, a wide passband filter is further realized. The proposed filter is fed by.a transducer composed of a microstrip line with a flaring ground. The simulated results show that the presented filter has an extremely wide upper stopband in addition to excellent passband filtering characteristics such as low loss, wide band, and high square ratio. A prototype passband filter is also fabricated to validate the predicted performances. The proposed spoof-SPPs filter is believed to be very promising for other surface waveguide components in microwave and terahertz bands.展开更多
A novel bandpass filter(BPF)based on spoof surface plasmon polaritons(SSPPs)using a compact folded slotline structure is proposed and experimentally demonstrated.The proposed novel SSPPs structure compared with a conv...A novel bandpass filter(BPF)based on spoof surface plasmon polaritons(SSPPs)using a compact folded slotline structure is proposed and experimentally demonstrated.The proposed novel SSPPs structure compared with a conventional plasmonic waveguide with slot line SSPPs unit structure at the same size,the considerable advantages in much lower asymptotic frequency with tight field confinement,which enable the proposed filter to be more miniaturization.A high-efficient mode conversion structure is designed to transition from TE-mode to SSPPs-mode by gradient slotline lengths.The low-frequency stop-band can be committed with microstrip to slotline evolution on both sides of the dielectric,while the high-frequency cutoff band is realized by the proposed SSPPs structure.The influence of dispersion relation,electric field distribution,surface current,and structural parameters on the transmission characteristics of the proposed BPF are analyzed by finite difference time domain(FDTD).To validate the design concept,the prototype of the miniaturized SSPPs BPF has been manufactured and measured.The experimental results show high performance of the fabricated sample,in which the working in a range of 0.9 GHz-5.2 GHz with the relative bandwidth is 142%,the insertion loss less than 0.5 dB,the reflection coefficient less than-10 dB,and the group delay is less than one ns.This works provides a mirror for realizing the miniaturization of waveguides,and the application and development of high-confinement SSPPs functional devices in the microwave and THz regimes.展开更多
This paper analyzes the influence of the global positionong system(GPS)spoofing attack(GSA)on phasor measurement units(PMU)measurements.We propose a detection method based on improved Capsule Neural Network(CapsNet)to...This paper analyzes the influence of the global positionong system(GPS)spoofing attack(GSA)on phasor measurement units(PMU)measurements.We propose a detection method based on improved Capsule Neural Network(CapsNet)to handle this attack.In the improved CapsNet,the gated recurrent unit(GRU)is added to the front of the full connection layer of the CapsNet.The improved CapsNet trains and updates the network parameters according to the historical measurements of the smart grid.The detection method uses different structures to extract the temporal and spatial features of the measurements simultaneously,which can accurately distinguish the attacked data from the normal data,to improve the detection accuracy.Finally,simulation experiments are carried out on IEEE 14-,IEEE 118-bus systems.The experimental results show that compared with other detection methods,our method is proved to be more efficient.展开更多
A novel leaky-wave antenna(LWA)utilizing spoof surface plasmon polaritons(SSPPs)excitation is proposed with continuous scanning range from endfire to forward.The designed transmission line unit supports two SSPPS mode...A novel leaky-wave antenna(LWA)utilizing spoof surface plasmon polaritons(SSPPs)excitation is proposed with continuous scanning range from endfire to forward.The designed transmission line unit supports two SSPPS modes,of which the 2nd order mode is applied in the design.A novel strategy has been devised to excite the spatial radiation of the-1st order harmonics by arranging periodic counter changed sinusoidal structures on both sides of the SSPPs transmission line.Both full-wave simulation and measurement results show that the proposed LWA presents wide scanning angle from endfire to forward.In the frequency range from 4 GHz to 10 GHz,LWAs achieve scanning from 90°to+20°,covering the entire backward quadrant continuously.展开更多
We propose a single-beam leaky-wave antenna(LWA) with a wide-scanning angle and a high-scanning rate based on spoof surface plasmon polariton(SSPP) in this paper. The SSPP transmission line(TL) is etched with periodic...We propose a single-beam leaky-wave antenna(LWA) with a wide-scanning angle and a high-scanning rate based on spoof surface plasmon polariton(SSPP) in this paper. The SSPP transmission line(TL) is etched with periodically arranged circular patches, which converts the slow-wave mode into the fast-wave region for radiation. The proposed LWA is designed, fabricated, and tested. The simulated results imply that the proposed LWA not only achieves a high radiation efficiency of about 81.4%, and a high scanning rate of 12.12, but also has a large scanning angle of 176° over a narrow operation bandwidth of 8.3-9.6 GHz(for |S_(11)| <-10 dB). In addition, the simulated average gain of the LWA can reach as high as 10.9 d Bi. The measured scanning angle range is 175° in the operation band of 8.2-9.6 GHz, and the measured average gain is 10.6 dBi. The experimental results are consistent with the simulation, validating its performance. An antenna with high radiation efficiency, wide scanning angle range, and high scanning rate has great potential for application in radar and wireless communication systems.展开更多
In recent years,with the rapid development of the drone industry,drones have been widely used in many fields such as aerial photography,plant protection,performance,and monitoring.To effectively control the unauthoriz...In recent years,with the rapid development of the drone industry,drones have been widely used in many fields such as aerial photography,plant protection,performance,and monitoring.To effectively control the unauthorized flight of drones,using GPS spoofing attacks to interfere with the flight of drones is a relatively simple and highly feasible attack method.However,the current method uses ground equipment to carry out spoofing attacks.The attack range is limited and the flexibility is not high.Based on the existing methods,this paper proposes a multi-UAV coordinated GPS spoofing scheme based on YOLO Nano,which can launch effective attacks against target drones with autonomous movement:First,a single-attack drone based on YOLO Nano is proposed.The target tracking scheme achieves accurate tracking of the target direction on a single-attack drone;then,based on the single-UAV target tracking,a multi-attack drone coordinated target tracking scheme based on the weighted least squares method is proposed to realize the target drone Finally,a new calculation method for false GPS signals is proposed,which adaptively adjusts the flight trajectory of the attacking drone and the content of the false GPS signal according to the autonomous movement of the target drone.展开更多
基金co-supported by the Tianjin Research innovation Project for Postgraduate Students,China(No.2022BKYZ039)the China Postdoctoral Science Foundation(No.2023M731788)the National Natural Science Foundation of China(No.62303246)。
文摘Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelator outputs.However,the accuracy of the delay estimation is limited by the spacing of the correlators.To address this,an innovative anti-spoofing method is introduced,which incorporates distinct coarse and refined stages for more accurate spoofing estimation.By leveraging the coarse delay estimates obtained through maximum likelihood estimation,the proposed method establishes the Windowed Sum of the Relative Delay(WSRD)statistics to detect the presence of spoofing signals.The iterative strategy is then employed to enhance the precision of the delay estimation.To further adapt to variations in the observation noise caused by spoofing intrusions and restore precise position,velocity,and timing solutions,an adaptive extended Kalman filter is proposed.This comprehensive framework offers detection,mitigation,and recovery against spoofing attacks.Experimental validation using datasets from the Texas Spoofing Test Battery(TEXBAT)demonstrates the effectiveness of the proposed anti-spoofing method.With 41 correlators,the method achieves a detection rate exceeding 90%at a false alarm rate of 10-5,with position or time errors below 15 m.Notably,this refined anti-spoofing approach shows robust detection and mitigation capabilities,requiring only a single antenna without the need for additional external sensors.These advancements can significantly contribute to the development of GNSS anti-spoofing measures.
基金supported in part by the Key Science and Technology Research of Henan Province(252102210239,242102211029,242102211105)the Henan Provincial Key Laboratory of Smart Lighting Open Fund(2023KF06)+2 种基金Zhumadian Science and Technology Youth Innovation Special Fund(QNZX202407)the Computer Basic Education Teaching Research Project of the National Research Society for Computer Basic Education in Higher Education Institutions(2024-AFCEC-393)the Young Backbone Teacher Support Program of Huanghuai University.
文摘With the widespread application of global navigation satellite system(GNSS),spoofing attacks pose a threat to the security and reliability of GNSS.It is of great significance to design effective GNSS spoofing detection technology to ensure the security and reliability of GNSS system applications for receiver users.Traditional spoofing detection techniques generally only determine whether a spoofing attack has occurred by monitoring the feature changes of one or two data information in the receiver.However,some spoofing modes can cleverly make the monitored data very close to the real data,thus avoiding these detection methods and easily making them ineffective.In this study,a GNSS spoofing jamming detection method based on hybrid kernel relevance vector machine(RVM)is proposed.The improved signal quality monitoring(SQM)movement variance,carrier noise ratio movement variance,pseudo range Doppler consistency,pseudorange residual,Doppler frequency,clock offset and clock drift are used as detection characteristics.This technology can detect GNSS spoofing signals,effectively improving the safety and reliability of GNSS systems.The experimental results show that this technology has high detection accuracy and anti-interference ability and can effectively respond to various forms of spoofing attacks.
基金partially supported by Asia Pacific University of Technology&Innovation(APU)Bukit Jalil,Kuala Lumpur,MalaysiaThe funding body had no role in the study design,data collection,analysis,interpretation,or writing of the manuscript.
文摘Kubernetes has become the dominant container orchestration platform,withwidespread adoption across industries.However,its default pod-to-pod communicationmechanism introduces security vulnerabilities,particularly IP spoofing attacks.Attackers can exploit this weakness to impersonate legitimate pods,enabling unauthorized access,lateral movement,and large-scale Distributed Denial of Service(DDoS)attacks.Existing security mechanisms such as network policies and intrusion detection systems introduce latency and performance overhead,making them less effective in dynamic Kubernetes environments.This research presents PodCA,an eBPF-based security framework designed to detect and prevent IP spoofing in real time while minimizing performance impact.PodCA integrates with Kubernetes’Container Network Interface(CNI)and uses eBPF to monitor and validate packet metadata at the kernel level.It maintains a container network mapping table that tracks pod IP assignments,validates packet legitimacy before forwarding,and ensures network integrity.If an attack is detected,PodCA automatically blocks spoofed packets and,in cases of repeated attempts,terminates compromised pods to prevent further exploitation.Experimental evaluation on an AWS Kubernetes cluster demonstrates that PodCA detects and prevents spoofed packets with 100%accuracy.Additionally,resource consumption analysis reveals minimal overhead,with a CPU increase of only 2–3%per node and memory usage rising by 40–60 MB.These results highlight the effectiveness of eBPF in securing Kubernetes environments with low overhead,making it a scalable and efficient security solution for containerized applications.
基金co-supported by the National Key Research and Development Program of China(No.2024YFE0107900)the National Natural Science Foundation of China(No.62222105)+1 种基金the Natural Science Foundation of Guangdong Province,China(No.2024A1515010235)the 2024 China Unicom Guangdong low-altitude communication and sensing key technology research and digital twin platform research and development project(No.20241890).
文摘Unmanned aerial vehicle(UAV)swarm network consisting of a collection of micro UAVs can be used for many applications.It is well established that packet routing is a fundamental problem to achieve UAV collaboration.However,the highly dynamic nature of UAVs,frequently changing network topologies and security issues,poses significant challenges to packet forwarding in UAV networks.The existing topology-based routing protocols are not well suited in UAV network due to their high controlling overhead or excessive end-to-end delay.Geographic routing is regarded as a promising solution,as it only requires local information.In order to enhance the accuracy and security of geographic routing in highly dynamic UAV network,in this paper,we propose a new predictive geographic(PGeo)routing strategy with location verification.First,a detection mechanism is adopted to recognize malicious UAVs falsifying their location.Then,an accurate average service time of a packet in the medium access control(MAC)layer is derived to assist location prediction.The proposed delay model can provide a theoretical basis for future work,and our simulation results reveal that PGeo outstrips the existing geographic routing protocols in terms of packet delivery ratio in the presence of location spoofing behavior.
基金supported in part by the National Natural Science Foundation of China(No.62271076)in part by the Fundamental Research Funds for the Central Universities,China(No.2242022k60006).
文摘The Global Positioning System(GPS)plays an indispensable role in the control of Unmanned Aerial Vehicle(UAV).However,the civilian GPS signals,transmitted over the air without any encryption,are vulnerable to spoofing attacks,which further guides the UAV on deviated positions or trajectories.To counter the GPS,,m spoofing on UAV system and to detect the position/trajectory anomaly in real time,a motion state vector based stack long short-term memory trajectory prediction scheme is firstly proposed,leveraging the temporal and spatial features of UAV kinematics.Based on the predicted results,an ensemble voting-based trajectory anomaly detection scheme is proposed to detect the position anomalies in real time with the information of motion state sequences.The proposed prediction-based trajectory anomaly detection scheme outperforms the existing offline detection schemes designed for fixed trajectories.Software In The Loop(SITL)based online prediction and online anomaly detection are demonstrated with random 3D flight trajectories.Results show that the coefficient of determination(R^(2))and Root Mean Square Error(RMSE)of the prediction scheme can reach 0.996 and 3.467,respectively.The accuracy,recall,and F1-score of the proposed anomaly detection scheme can reach 0.984,0.988,and 0.983,respectively,which outperform deep ensemble learning,LSTM-based classifier,machine learning classifier and GA-XGBoost based schemes.Moreover,results show that compared with LSTM-based classifier,the average duration(from the moment starting an attack to the moment the attack being detected)and distance of the proposed scheme are reduced by 24.4%and 19.5%,respectively.
基金supported in part by the Natural Science Foundation of Tianjin(No.19JCYBJC16100)the Tianjin Innovation and Entrepreneurship Training Program(No.202210060027)。
文摘A triple-band miniaturized end-fire antenna based on the odd modes of spoof surface plasmonic polariton(SSPP)waveguide resonator is proposed in this paper.To meet the ever increasing demand for more communication channels and less antenna sizes,multi-band antennas are currently under intensive investigation.By a novel feeding method,three odd modes are excited on an SSPP waveguide resonator,which performs as an end-fire antenna operating at three bands,7.15-7.26 GHz,11.6-12.2 GHz and 13.5-13.64 GHz.It exhibits reasonably high and stable maximum gains of 5.26 dBi,7.97 dBi and 10.1 dBi and maximum efficiencies of 64%,92%and 98%at the three bands,respectively.Moreover,in the second band,the main beam angle shows a frequency dependence with a total scanning angle of 19°.The miniaturized triple-band antenna has a great potential in wireless communication systems,satellite communication and radar systems.
基金The National Natural Science Foundation of China(No.61271214,61471152)the Postdoctoral Science Foundation of Jiangsu Province(No.1402023C)the Natural Science Foundation of Zhejiang Province(No.LZ14F010003)
文摘In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the GNSS spoofing is proposed.First,a Hammerstein model is applied to model the spoofer/GNSS transmitter and the wireless channel.Then,a novel method based on the uncultivated wolf pack algorithm（UWPA） is proposed to estimate the model parameters.Taking the estimated model parameters as a feature vector,the identification of the spoofing is realized by comparing the Euclidean distance between the feature vectors.Simulations verify the effectiveness and the robustness of the proposed method.The results show that,compared with the other identification algorithms,such as least square（LS）,the iterative method and the bat-inspired algorithm（BA）,although the UWPA has a little more time-eomplexity than the LS and the BA algorithm,it has better estimation precision of the model parameters and higher identification rate of the GNSS spoofing,even for relative low signal-to-noise ratios.
基金supported by the National Natural Science Foundation of China(41804035,41374027)。
文摘The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.
基金supported by the State Key Laboratory of Geo-Information Engineering(SKLGIE2022-Z-2-1)the National Natural Science Foundation of China(41674024,42174036).
文摘Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.
基金supported in part by the National Key R&D Program of China(No.2022YFB3904503)National Natural Science Foundation of China(No.62172418)。
文摘The BeiDou-Ⅱcivil navigation message(BDⅡ-CNAV)is transmitted in an open environment and no information integrity protection measures are provided.Hence,the BDⅡ-CNAV faces the threat of spoofing attacks,which can lead to wrong location reports and time indication.In order to deal with this threat,we proposed a scheme of anti-spoofing for BDⅡ-CNAV based on integrated information authentication.This scheme generates two type authentication information,one is authentication code information(ACI),which is applied to confirm the authenticity and reliability of satellite time information,and the other is signature information,which is used to authenticate the integrity of satellite location information and other information.Both authentication information is designed to embed into the reserved bits in BDⅡ-CNAV without changing the frame structure.In order to avoid authentication failure caused by public key error or key error,the key or public key prompt information(KPKPI)are designed to remind the receiver to update both keys in time.Experimental results indicate that the scheme can successfully detect spoofing attacks,and the authentication delay is less than 1%of the transmission delay,which meets the requirements of BDⅡ-CNAV information authentication.
文摘This paper presents a new approach to estimate the true position of an unmanned aerial vehicle （UAV） in the conditions of spoofing attacks on global positioning system （GPS） receivers. This approach consists of two phases, the spoofing detection phase which is accomplished by hypothesis test and the trajectory estimation phase which is carried out by applying the adapted particle filters to the integrated inertial navigation system （INS） and GPS. Due to nonlinearity and unfavorable impacts of spoofing signals on GPS receivers, deviation in position calculation is modeled as a cumulative uniform error. This paper also presents a procedure of applying adapted particle swarm optimization filter （PSOF） to the INS/GPS integration system as an estimator to compensate spoofing attacks. Due to memory based nature of PSOF and benefits of each particle＇s experiences, application of PSOF algorithm in the INS/GPS integ- ration system leads to more precise positioning compared with general particle filter （PF） and adaptive unscented particle filer （AUPF） in the GPS spoofing attack scenarios. Simulation results show that the adapted PSOF algorithm is more reliable and accurate in estim- ating the true position of UAV in the condition of spoofing attacks. The validation of the proposed method is done by root mean square error （RMSE） test.
基金This work was supported in part by NSF under Grants CNS-1950704,CNS-1828593,and OAC-1829771,ONR under Grant N00014-20-1-2065,NSA under Grant H98230-21-1-0278,and the Commonwealth Cyber Initiative.
文摘The Global Positioning System(GPS)has become a foundation for most location-based services and navigation systems,such as autonomous vehicles,drones,ships,and wearable devices.However,it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools.Pervasive tools,such as Fake GPS,Lockito,and software-defined radio,enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected.Furthermore,it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors.To this end,we propose DeepPOSE,a deep learning model,to address the noise introduced in sensor readings and detect GPS spoofing attacks on mobile platforms.Our design uses a convolutional and recurrent neural network to reduce the noise,to recover a vehicle's real-time trajectory from multiple sensor inputs.We further propose a novel scheme to map the constructed trajectory from sensor readings onto the Google map,to smartly eliminate the accumulation of errors on the trajectory estimation.The reconstructed trajectory from sensors is then used to detect the GPS spoofing attack.Compared with the existing method,the proposed approach demonstrates a significantly higher degree of accuracy for detecting GPS spoofing attacks.
基金Project supported by the Key Grant Project of Ministry of Education of China(Grant No.313029)the FDCT Research Grant from Macao Science and Technology Development Fund,China(Grant No.051/2014/A1)the Multi-Year Research Grant from University of Macao,Macao SAR,China(Grant No.MYRG2014-00079-FST)
文摘We investigate the guiding modes of spoof surface plasmon polaritons （SPPs） on a symmetric ultra-thin plasmonic structure. From the analysis, we deduce the operating frequency region of the single-mode propagation. Based on this property, a spoof SPPs lowpass filter is then constituted in the microwave frequency. By introducing a transmission zero at the lower frequency band using a pair of stepped-impedance stubs, a wide passband filter is further realized. The proposed filter is fed by.a transducer composed of a microstrip line with a flaring ground. The simulated results show that the presented filter has an extremely wide upper stopband in addition to excellent passband filtering characteristics such as low loss, wide band, and high square ratio. A prototype passband filter is also fabricated to validate the predicted performances. The proposed spoof-SPPs filter is believed to be very promising for other surface waveguide components in microwave and terahertz bands.
基金the National Natural Science Foundation of China(Grant Nos.62071221 and 62071442)the Equipment Advance Research Foundation of China(Grant No.80909010302)the Key Laboratory of Radar Imaging and Microwave Photonics(Nanjing University of Aeronautics and Astronautics),Ministry of Education of China(Grant No.NJ20210006).
文摘A novel bandpass filter(BPF)based on spoof surface plasmon polaritons(SSPPs)using a compact folded slotline structure is proposed and experimentally demonstrated.The proposed novel SSPPs structure compared with a conventional plasmonic waveguide with slot line SSPPs unit structure at the same size,the considerable advantages in much lower asymptotic frequency with tight field confinement,which enable the proposed filter to be more miniaturization.A high-efficient mode conversion structure is designed to transition from TE-mode to SSPPs-mode by gradient slotline lengths.The low-frequency stop-band can be committed with microstrip to slotline evolution on both sides of the dielectric,while the high-frequency cutoff band is realized by the proposed SSPPs structure.The influence of dispersion relation,electric field distribution,surface current,and structural parameters on the transmission characteristics of the proposed BPF are analyzed by finite difference time domain(FDTD).To validate the design concept,the prototype of the miniaturized SSPPs BPF has been manufactured and measured.The experimental results show high performance of the fabricated sample,in which the working in a range of 0.9 GHz-5.2 GHz with the relative bandwidth is 142%,the insertion loss less than 0.5 dB,the reflection coefficient less than-10 dB,and the group delay is less than one ns.This works provides a mirror for realizing the miniaturization of waveguides,and the application and development of high-confinement SSPPs functional devices in the microwave and THz regimes.
文摘This paper analyzes the influence of the global positionong system(GPS)spoofing attack(GSA)on phasor measurement units(PMU)measurements.We propose a detection method based on improved Capsule Neural Network(CapsNet)to handle this attack.In the improved CapsNet,the gated recurrent unit(GRU)is added to the front of the full connection layer of the CapsNet.The improved CapsNet trains and updates the network parameters according to the historical measurements of the smart grid.The detection method uses different structures to extract the temporal and spatial features of the measurements simultaneously,which can accurately distinguish the attacked data from the normal data,to improve the detection accuracy.Finally,simulation experiments are carried out on IEEE 14-,IEEE 118-bus systems.The experimental results show that compared with other detection methods,our method is proved to be more efficient.
文摘A novel leaky-wave antenna(LWA)utilizing spoof surface plasmon polaritons(SSPPs)excitation is proposed with continuous scanning range from endfire to forward.The designed transmission line unit supports two SSPPS modes,of which the 2nd order mode is applied in the design.A novel strategy has been devised to excite the spatial radiation of the-1st order harmonics by arranging periodic counter changed sinusoidal structures on both sides of the SSPPs transmission line.Both full-wave simulation and measurement results show that the proposed LWA presents wide scanning angle from endfire to forward.In the frequency range from 4 GHz to 10 GHz,LWAs achieve scanning from 90°to+20°,covering the entire backward quadrant continuously.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 62171460 and 61801508)the Natural Science Basic Research Program of Shaanxi Province, China (Grant Nos. 2020JM-350, 20200108, 20210110, and 2020022)the Postdoctoral Innovative Talents Support Program of China (Grant Nos. BX20180375, 2019M653960, and 2021T140111)。
文摘We propose a single-beam leaky-wave antenna(LWA) with a wide-scanning angle and a high-scanning rate based on spoof surface plasmon polariton(SSPP) in this paper. The SSPP transmission line(TL) is etched with periodically arranged circular patches, which converts the slow-wave mode into the fast-wave region for radiation. The proposed LWA is designed, fabricated, and tested. The simulated results imply that the proposed LWA not only achieves a high radiation efficiency of about 81.4%, and a high scanning rate of 12.12, but also has a large scanning angle of 176° over a narrow operation bandwidth of 8.3-9.6 GHz(for |S_(11)| <-10 dB). In addition, the simulated average gain of the LWA can reach as high as 10.9 d Bi. The measured scanning angle range is 175° in the operation band of 8.2-9.6 GHz, and the measured average gain is 10.6 dBi. The experimental results are consistent with the simulation, validating its performance. An antenna with high radiation efficiency, wide scanning angle range, and high scanning rate has great potential for application in radar and wireless communication systems.
基金This work is supported by the National Natural Science Foundation of China under Grants U1836110,U1836208by the Jiangsu Basic Research Programs-Natural Science Foundation under Grant No.BK20200039。
文摘In recent years,with the rapid development of the drone industry,drones have been widely used in many fields such as aerial photography,plant protection,performance,and monitoring.To effectively control the unauthorized flight of drones,using GPS spoofing attacks to interfere with the flight of drones is a relatively simple and highly feasible attack method.However,the current method uses ground equipment to carry out spoofing attacks.The attack range is limited and the flexibility is not high.Based on the existing methods,this paper proposes a multi-UAV coordinated GPS spoofing scheme based on YOLO Nano,which can launch effective attacks against target drones with autonomous movement:First,a single-attack drone based on YOLO Nano is proposed.The target tracking scheme achieves accurate tracking of the target direction on a single-attack drone;then,based on the single-UAV target tracking,a multi-attack drone coordinated target tracking scheme based on the weighted least squares method is proposed to realize the target drone Finally,a new calculation method for false GPS signals is proposed,which adaptively adjusts the flight trajectory of the attacking drone and the content of the false GPS signal according to the autonomous movement of the target drone.
