Synchrophasor measurements are essential to realtime situational awareness of the smart grid but vulnerable to cyber-attacks during the process of transmission and invocation.To ensure data security and mitigate the i...Synchrophasor measurements are essential to realtime situational awareness of the smart grid but vulnerable to cyber-attacks during the process of transmission and invocation.To ensure data security and mitigate the impact of spoofed synchrophasor measurements,this work proposes a novel object detection method using a Weight-based One-dimensional Convolutional Segmentation Network(WOCSN)with the ability of attack behavior identification and time localization.In WOCSN,automatic data feature extraction can be achieved by onedimensional convolution from the input signal,thereby reducing the impact of handcrafted features.A weight loss function is designed to distribute the contribution for normal and attack signals.Then,attack time is located via the proposed binary method based on pixel segmentation.Furthermore,the actual synchrophasor data collected from four locations are used for the performance evaluation of the WOCSN.Finally,combined with designed evaluation metrics,the time localization ability of WOCSN is validated in the scenarios of composite attacks with different spoofed intensities and time-sensitivities.展开更多
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
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
The Industrial Internet of Things(IIoT)is increasingly vulnerable to sophisticated cyber threats,particularly zero-day attacks that exploit unknown vulnerabilities and evade traditional security measures.To address th...The Industrial Internet of Things(IIoT)is increasingly vulnerable to sophisticated cyber threats,particularly zero-day attacks that exploit unknown vulnerabilities and evade traditional security measures.To address this critical challenge,this paper proposes a dynamic defense framework named Zero-day-aware Stackelberg Game-based Multi-Agent Distributed Deep Deterministic Policy Gradient(ZSG-MAD3PG).The framework integrates Stackelberg game modeling with the Multi-Agent Distributed Deep Deterministic Policy Gradient(MAD3PG)algorithm and incorporates defensive deception(DD)strategies to achieve adaptive and efficient protection.While conventional methods typically incur considerable resource overhead and exhibit higher latency due to static or rigid defensive mechanisms,the proposed ZSG-MAD3PG framework mitigates these limitations through multi-stage game modeling and adaptive learning,enabling more efficient resource utilization and faster response times.The Stackelberg-based architecture allows defenders to dynamically optimize packet sampling strategies,while attackers adjust their tactics to reach rapid equilibrium.Furthermore,dynamic deception techniques reduce the time required for the concealment of attacks and the overall system burden.A lightweight behavioral fingerprinting detection mechanism further enhances real-time zero-day attack identification within industrial device clusters.ZSG-MAD3PG demonstrates higher true positive rates(TPR)and lower false alarm rates(FAR)compared to existing methods,while also achieving improved latency,resource efficiency,and stealth adaptability in IIoT zero-day defense scenarios.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
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
Resonantly enhanced dielectric sensing has superior sensitivity and accuracy because the signal is measured from relative resonance shifts that are immune to signal fluctuations.For applications in the Internet of Thi...Resonantly enhanced dielectric sensing has superior sensitivity and accuracy because the signal is measured from relative resonance shifts that are immune to signal fluctuations.For applications in the Internet of Things(IoT),accurate detection of resonance frequency shifts using a compact circuit is in high demand.We proposed an ultracompact integrated sensing system that merges a spoof surface plasmon resonance sensor with signal detection,processing,and wireless communication.A softwaredefined scheme was developed to track the resonance shift,which minimized the hardware circuit and made the detection adaptive to the target resonance.A microwave spoof surface plasmon resonator was designed to enhance sensitivity and resonance intensity.The integrated sensing system was constructed on a printed circuit board with dimensions of 1.8 cm×1.2 cm and connected to a smartphone wirelessly through Bluetooth,working in both frequency scanning mode and resonance tracking mode and achieving a signal-to-noise ratio of 69 dB in acetone vapor sensing.This study provides an ultracompact,accurate,adaptive,sensitive,and wireless solution for resonant sensors in the IoT.展开更多
In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in th...In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in the signals across different incident directions,resulting in distinct CNR variations for each signal.A model is developed to calculate the variation value of the signal CNR based on the antenna gain pattern.This model enables the differentiation of the variation values of the CNR for authentic satellite signals and spoofing signals,thereby facilitating spoofing detection.The proposed method is capable of detecting spoofing signals with power and CNR similar to those of authentic satellite signals.The accuracy of the signal CNR variation value calculation model and the effectiveness of the spoofing detection method are verified through a series of experiments.In addition,the proposed spoofing detection method works not only for a single spoofing source but also for distributed spoofing sources.展开更多
Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while bla...Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while black-box attacks are proposed without such information to meet practical situations.Existing black-box attacks improve trans-ferability by integrating multiple models or training on multiple datasets,but these methods are costly.Motivated by the optimisation strategy with spatial information on the perturbed paths and samples,we propose a Dual Spatial Momentum Iterative Fast Gradient Sign Method(DS-MI-FGSM)to improve the transferability of black-box at-tacks against SRSs.Specifically,DS-MI-FGSM only needs a single data and one model as the input;by extending to the data and model neighbouring spaces,it generates adver-sarial examples against the integrating models.To reduce the risk of overfitting,DS-MI-FGSM also introduces gradient masking to improve transferability.The authors conduct extensive experiments regarding the speaker recognition task,and the results demonstrate the effectiveness of their method,which can achieve up to 92%attack success rate on the victim model in black-box scenarios with only one known model.展开更多
The Internet of Things(IoT)has permeated various fields relevant to our lives.In these applications,countless IoT devices transmit vast amounts of data,which often carry important and private information.To prevent ma...The Internet of Things(IoT)has permeated various fields relevant to our lives.In these applications,countless IoT devices transmit vast amounts of data,which often carry important and private information.To prevent malicious users from spoofing these information,the first critical step is effective authentication.Physical Layer Authentication(PLA)employs unique characteristics inherent to wireless signals and physical devices and is promising in the IoT due to its flexibility,low complexity,and transparency to higher layer protocols.In this paper,the focus is on the interaction between multiple malicious spoofers and legitimate receivers in the PLA process.First,the interaction is formulated as a static spoof detection game by including the spoofers and receivers as players.The best authentication threshold of the receiver and the attack rate of the spoofers are consideblack as Nash Equilibrium(NE).Then,closed-form expressions are derived for all NEs in the static environment in three cases:multiplayer games,zero-sum games with collisions,and zero-sum games without collisions.Considering the dynamic environment,a Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm is proposed to analyze the interactions of receiver and spoofers.Last,comprehensive simulation experiments are conducted and demonstrate the impact of environmental parameters on the NEs,which provides guidance to design effective PLA schemes.展开更多
Recent breakthroughs in the field of non-Hermitian physics present unprecedented opportunities,from fundamental theories to cutting-edge applications such as multimode lasers,unconventional wave transport,and high-per...Recent breakthroughs in the field of non-Hermitian physics present unprecedented opportunities,from fundamental theories to cutting-edge applications such as multimode lasers,unconventional wave transport,and high-performance sensors.The exceptional point,a spectral singularity widely existing in non-Hermitian systems,provides an indispensable route to enhance the sensitivity of optical detection.However,the exceptional point of the forementioned systems is set once the system is built or fabricated,and machining errors make it hard to reach such a state precisely.To this end,we develop a highly tunable and reconfigurable exceptional point system,i.e.,a single spoof plasmonic resonator suspended above a substrate and coupled with two freestanding Rayleigh scatterers.Our design offers great flexibility to control exceptional point states,enabling us to dynamically reconfigure the exceptional point formed by various multipolar modes across a broadband frequency range.Specifically,we experimentally implement five distinct exceptional points by precisely manipulating the positions of two movable Rayleigh scatterers.In addition,the enhanced perturbation strength offers remarkable sensitivity enhancement for detecting deep-subwavelength particles with the minimum dimension down to 0.001λ(withλto be the free-space wavelength).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 hidden danger of the automatic speaker verification(ASV)system is various spoofed speeches.These threats can be classified into two categories,namely logical access(LA)and physical access(PA).To improve identifica...The hidden danger of the automatic speaker verification(ASV)system is various spoofed speeches.These threats can be classified into two categories,namely logical access(LA)and physical access(PA).To improve identification capability of spoofed speech detection,this paper considers the research on features.Firstly,following the idea of modifying the constant-Q-based features,this work considered adding variance or mean to the constant-Q-based cepstral domain to obtain good performance.Secondly,linear frequency cepstral coefficients(LFCCs)performed comparably with constant-Q-based features.Finally,we proposed linear frequency variance-based cepstral coefficients(LVCCs)and linear frequency mean-based cepstral coefficients(LMCCs)for identification of speech spoofing.LVCCs and LMCCs could be attained by adding the frame variance or the mean to the log magnitude spectrum based on LFCC features.The proposed novel features were evaluated on ASVspoof 2019 datase.The experimental results show that compared with known hand-crafted features,LVCCs and LMCCs are more effective in resisting spoofed speech attack.展开更多
Position-spoofing-based attacks seriously threaten the security of Vehicular Ad Hoc Network(VANET).An effective solution to detect position spoofing is location verification.However,since vehicles move fast and the to...Position-spoofing-based attacks seriously threaten the security of Vehicular Ad Hoc Network(VANET).An effective solution to detect position spoofing is location verification.However,since vehicles move fast and the topology changes quickly in VANET,the static location verification method in Wireless Sensor Network(WSN) is not suitable for VANET.Taking into account the dynamic changing topology of VANET and collusion,we propose a Time-Slice-based Location Verification scheme,named TSLV,to resist position spoofing in VANET.Specifically,TSLV transforms the dynamic topology into static topology by time slice and each time slice corresponds to a verification process.The verifier can implement location verification for the corresponding prover.During the verification process,the verifier first filters out vehicles which provide unreasonably claimed locations,and then uses the Mean Square Error(MSE)-based cluster approach to separate the consistent vehicles by time slice,and uses the consistent set for its verification.In addition,security analysis and simulation show that TSLV can defend against the collusion attack effectively.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 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
基金This work is supported in part by the CURENT Industry Partnership Program,in part by the Engineering Research Center Program of the National Science Foundation,DOE under NSF Award Number EEC-1041877in part by the National Natural Science Foundation of China under award number 52177078in part with the project funded by China Postdoctoral Science Foundation under award number BX20220102.
文摘Synchrophasor measurements are essential to realtime situational awareness of the smart grid but vulnerable to cyber-attacks during the process of transmission and invocation.To ensure data security and mitigate the impact of spoofed synchrophasor measurements,this work proposes a novel object detection method using a Weight-based One-dimensional Convolutional Segmentation Network(WOCSN)with the ability of attack behavior identification and time localization.In WOCSN,automatic data feature extraction can be achieved by onedimensional convolution from the input signal,thereby reducing the impact of handcrafted features.A weight loss function is designed to distribute the contribution for normal and attack signals.Then,attack time is located via the proposed binary method based on pixel segmentation.Furthermore,the actual synchrophasor data collected from four locations are used for the performance evaluation of the WOCSN.Finally,combined with designed evaluation metrics,the time localization ability of WOCSN is validated in the scenarios of composite attacks with different spoofed intensities and time-sensitivities.
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funded in part by the Humanities and Social Sciences Planning Foundation of Ministry of Education of China under Grant No.24YJAZH123National Undergraduate Innovation and Entrepreneurship Training Program of China under Grant No.202510347069the Huzhou Science and Technology Planning Foundation under Grant No.2023GZ04.
文摘The Industrial Internet of Things(IIoT)is increasingly vulnerable to sophisticated cyber threats,particularly zero-day attacks that exploit unknown vulnerabilities and evade traditional security measures.To address this critical challenge,this paper proposes a dynamic defense framework named Zero-day-aware Stackelberg Game-based Multi-Agent Distributed Deep Deterministic Policy Gradient(ZSG-MAD3PG).The framework integrates Stackelberg game modeling with the Multi-Agent Distributed Deep Deterministic Policy Gradient(MAD3PG)algorithm and incorporates defensive deception(DD)strategies to achieve adaptive and efficient protection.While conventional methods typically incur considerable resource overhead and exhibit higher latency due to static or rigid defensive mechanisms,the proposed ZSG-MAD3PG framework mitigates these limitations through multi-stage game modeling and adaptive learning,enabling more efficient resource utilization and faster response times.The Stackelberg-based architecture allows defenders to dynamically optimize packet sampling strategies,while attackers adjust their tactics to reach rapid equilibrium.Furthermore,dynamic deception techniques reduce the time required for the concealment of attacks and the overall system burden.A lightweight behavioral fingerprinting detection mechanism further enhances real-time zero-day attack identification within industrial device clusters.ZSG-MAD3PG demonstrates higher true positive rates(TPR)and lower false alarm rates(FAR)compared to existing methods,while also achieving improved latency,resource efficiency,and stealth adaptability in IIoT zero-day defense scenarios.
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.
基金supported by the National Natural Science Foundation of China(62288101,61701108,and 61631007)the National Key Research and Development Program of China(2017YFA0700201,2017YFA0700202,and 2017YFA0700203)+1 种基金the Major Project of Natural Science Foundation of Jiangsu Province(BK20212002)the 111 Project(111-2-05).
文摘Resonantly enhanced dielectric sensing has superior sensitivity and accuracy because the signal is measured from relative resonance shifts that are immune to signal fluctuations.For applications in the Internet of Things(IoT),accurate detection of resonance frequency shifts using a compact circuit is in high demand.We proposed an ultracompact integrated sensing system that merges a spoof surface plasmon resonance sensor with signal detection,processing,and wireless communication.A softwaredefined scheme was developed to track the resonance shift,which minimized the hardware circuit and made the detection adaptive to the target resonance.A microwave spoof surface plasmon resonator was designed to enhance sensitivity and resonance intensity.The integrated sensing system was constructed on a printed circuit board with dimensions of 1.8 cm×1.2 cm and connected to a smartphone wirelessly through Bluetooth,working in both frequency scanning mode and resonance tracking mode and achieving a signal-to-noise ratio of 69 dB in acetone vapor sensing.This study provides an ultracompact,accurate,adaptive,sensitive,and wireless solution for resonant sensors in the IoT.
基金supported by the National Natural Science Foundation of China(62273195).
文摘In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in the signals across different incident directions,resulting in distinct CNR variations for each signal.A model is developed to calculate the variation value of the signal CNR based on the antenna gain pattern.This model enables the differentiation of the variation values of the CNR for authentic satellite signals and spoofing signals,thereby facilitating spoofing detection.The proposed method is capable of detecting spoofing signals with power and CNR similar to those of authentic satellite signals.The accuracy of the signal CNR variation value calculation model and the effectiveness of the spoofing detection method are verified through a series of experiments.In addition,the proposed spoofing detection method works not only for a single spoofing source but also for distributed spoofing sources.
基金The Major Key Project of PCL,Grant/Award Number:PCL2022A03National Natural Science Foundation of China,Grant/Award Numbers:61976064,62372137Zhejiang Provincial Natural Science Foundation of China,Grant/Award Number:LZ22F020007。
文摘Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while black-box attacks are proposed without such information to meet practical situations.Existing black-box attacks improve trans-ferability by integrating multiple models or training on multiple datasets,but these methods are costly.Motivated by the optimisation strategy with spatial information on the perturbed paths and samples,we propose a Dual Spatial Momentum Iterative Fast Gradient Sign Method(DS-MI-FGSM)to improve the transferability of black-box at-tacks against SRSs.Specifically,DS-MI-FGSM only needs a single data and one model as the input;by extending to the data and model neighbouring spaces,it generates adver-sarial examples against the integrating models.To reduce the risk of overfitting,DS-MI-FGSM also introduces gradient masking to improve transferability.The authors conduct extensive experiments regarding the speaker recognition task,and the results demonstrate the effectiveness of their method,which can achieve up to 92%attack success rate on the victim model in black-box scenarios with only one known model.
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant 2022YJS008 and Grant 2019JBZ001in part by the National Natural Science Foundation of China under Grant 61931001 and Grant 61871023in part by the Beijing Natural Science Foundation under Grant 4202054。
文摘The Internet of Things(IoT)has permeated various fields relevant to our lives.In these applications,countless IoT devices transmit vast amounts of data,which often carry important and private information.To prevent malicious users from spoofing these information,the first critical step is effective authentication.Physical Layer Authentication(PLA)employs unique characteristics inherent to wireless signals and physical devices and is promising in the IoT due to its flexibility,low complexity,and transparency to higher layer protocols.In this paper,the focus is on the interaction between multiple malicious spoofers and legitimate receivers in the PLA process.First,the interaction is formulated as a static spoof detection game by including the spoofers and receivers as players.The best authentication threshold of the receiver and the attack rate of the spoofers are consideblack as Nash Equilibrium(NE).Then,closed-form expressions are derived for all NEs in the static environment in three cases:multiplayer games,zero-sum games with collisions,and zero-sum games without collisions.Considering the dynamic environment,a Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm is proposed to analyze the interactions of receiver and spoofers.Last,comprehensive simulation experiments are conducted and demonstrate the impact of environmental parameters on the NEs,which provides guidance to design effective PLA schemes.
基金supported by the National Natural Science Foundation of China(Grant Nos.61871215,61771238,and 61701246)the National Key Research and Development Program of China(Grant No.2022YFA1404903)+9 种基金the Fund of Qing Lan Project of Jiangsu Province(Grant No.1004-YQR22031)the Six Talent Peaks Project in Jiangsu Province(Grant No.2018-GDZB-009)the Fund of Prospective Layout of Scientific Research for NUAA(Nanjing University of Aeronautics and Astronautics)(Grant Nos.1004-ILA22002 and 1004-ILA22068)the Research and Practice Innovation Program of Nanjing University of Aeronautics and Astronautics(Grant No.xcxjh20210408)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX22_0364)the Fundamental Research Funds for the Central Universities,NUAA(Grant No.NS2023022)the Nanjing University of Aeronautics and Astronautics Startup Grant(Grant No.1004-YQR23031)the Distinguished Professor Fund of Jiangsu Province(Grant No.1004-YQR24010)Fundamental Research Funds for the Central Universities,NUAA(No.NE2024007)the Singapore National Research Foundation Competitive Research Program(NRF-CRP22-2019-0006).
文摘Recent breakthroughs in the field of non-Hermitian physics present unprecedented opportunities,from fundamental theories to cutting-edge applications such as multimode lasers,unconventional wave transport,and high-performance sensors.The exceptional point,a spectral singularity widely existing in non-Hermitian systems,provides an indispensable route to enhance the sensitivity of optical detection.However,the exceptional point of the forementioned systems is set once the system is built or fabricated,and machining errors make it hard to reach such a state precisely.To this end,we develop a highly tunable and reconfigurable exceptional point system,i.e.,a single spoof plasmonic resonator suspended above a substrate and coupled with two freestanding Rayleigh scatterers.Our design offers great flexibility to control exceptional point states,enabling us to dynamically reconfigure the exceptional point formed by various multipolar modes across a broadband frequency range.Specifically,we experimentally implement five distinct exceptional points by precisely manipulating the positions of two movable Rayleigh scatterers.In addition,the enhanced perturbation strength offers remarkable sensitivity enhancement for detecting deep-subwavelength particles with the minimum dimension down to 0.001λ(withλto be the free-space wavelength).
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National Natural Science Foundation of China(No.62001100)。
文摘The hidden danger of the automatic speaker verification(ASV)system is various spoofed speeches.These threats can be classified into two categories,namely logical access(LA)and physical access(PA).To improve identification capability of spoofed speech detection,this paper considers the research on features.Firstly,following the idea of modifying the constant-Q-based features,this work considered adding variance or mean to the constant-Q-based cepstral domain to obtain good performance.Secondly,linear frequency cepstral coefficients(LFCCs)performed comparably with constant-Q-based features.Finally,we proposed linear frequency variance-based cepstral coefficients(LVCCs)and linear frequency mean-based cepstral coefficients(LMCCs)for identification of speech spoofing.LVCCs and LMCCs could be attained by adding the frame variance or the mean to the log magnitude spectrum based on LFCC features.The proposed novel features were evaluated on ASVspoof 2019 datase.The experimental results show that compared with known hand-crafted features,LVCCs and LMCCs are more effective in resisting spoofed speech attack.
基金supported by National Natural Science Foundation of China under Grant No.60972036
文摘Position-spoofing-based attacks seriously threaten the security of Vehicular Ad Hoc Network(VANET).An effective solution to detect position spoofing is location verification.However,since vehicles move fast and the topology changes quickly in VANET,the static location verification method in Wireless Sensor Network(WSN) is not suitable for VANET.Taking into account the dynamic changing topology of VANET and collusion,we propose a Time-Slice-based Location Verification scheme,named TSLV,to resist position spoofing in VANET.Specifically,TSLV transforms the dynamic topology into static topology by time slice and each time slice corresponds to a verification process.The verifier can implement location verification for the corresponding prover.During the verification process,the verifier first filters out vehicles which provide unreasonably claimed locations,and then uses the Mean Square Error(MSE)-based cluster approach to separate the consistent vehicles by time slice,and uses the consistent set for its verification.In addition,security analysis and simulation show that TSLV can defend against the collusion attack effectively.
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.
