Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant ...Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI.展开更多
The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhan...The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhance spectrum utilization by accessing unused spectrum when licensed Primary Mobile Equipment(PME)is inactive or served by a Primary Base Station(PrBS).Secondary Mobile Equipment(SME)accesses this spectrum through a Secondary Base Station(SrBS)using opportunistic access,i.e.,spectrum sensing.Hybrid Multiple Access(HMA),combining Orthogonal Multiple Access(OMA)and Non-Orthogonal Multiple Access(NOMA),can enhance Energy Efficiency(EE).Additionally,SME Clustering(SMEC)reduces inter-cluster interference,enhancing EE further.Despite these advancements,the integration of CR technology,HMA,and SMEC in CRN for better bandwidth utilization and EE remains unexplored.This paper introduces a new CRassisted SMEC-based Downlink HMA(CR-SMEC-DHMA)method for 6G CRN,aimed at jointly optimizing SME admission,SME association,sum rate,and EE subject to imperfect sensing,collision,and Quality of Service(QoS).A novel optimization problem,formulated as a non-linear fractional programming problem,is solved using the Charnes-Cooper Transformation(CCT)to convert into a concave optimization problem,and an𝜖-optimal Outer Approximation Algorithm(OAA)is employed to solve the concave optimization problem.Simulations demonstrate the effectiveness of the proposed CR-SMEC-DHMA,surpassing the performance of current OMAenabled CRN,NOMA-enabled CRN,SMEC-OMA enabled CRN,and SMEC-NOMA enabled CRN methods,with ε-optimal results obtained at ε=10^(−3),while satisfying Performance Measures(PMs)including SME admission in SMEC,SME association with SrBS,SME-channel opportunistic allocation through spectrum sensing,sum rate and overall EE within the 6G CRN.展开更多
Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the network.IPv6 has introduced new features like Neighbour Discovery Protocol(NDP)and A...Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the network.IPv6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration Scheme.IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications.Therefore,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of features.This paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential features.Moreover,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios.The results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)features.The proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.展开更多
6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is...6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques.展开更多
基金supported by the National Key R&D Program of China(Grant No.2022YFA1005000)the National Natural Science Foundation of China(Grant No.62025110 and 62101308).
文摘Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI.
文摘The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhance spectrum utilization by accessing unused spectrum when licensed Primary Mobile Equipment(PME)is inactive or served by a Primary Base Station(PrBS).Secondary Mobile Equipment(SME)accesses this spectrum through a Secondary Base Station(SrBS)using opportunistic access,i.e.,spectrum sensing.Hybrid Multiple Access(HMA),combining Orthogonal Multiple Access(OMA)and Non-Orthogonal Multiple Access(NOMA),can enhance Energy Efficiency(EE).Additionally,SME Clustering(SMEC)reduces inter-cluster interference,enhancing EE further.Despite these advancements,the integration of CR technology,HMA,and SMEC in CRN for better bandwidth utilization and EE remains unexplored.This paper introduces a new CRassisted SMEC-based Downlink HMA(CR-SMEC-DHMA)method for 6G CRN,aimed at jointly optimizing SME admission,SME association,sum rate,and EE subject to imperfect sensing,collision,and Quality of Service(QoS).A novel optimization problem,formulated as a non-linear fractional programming problem,is solved using the Charnes-Cooper Transformation(CCT)to convert into a concave optimization problem,and an𝜖-optimal Outer Approximation Algorithm(OAA)is employed to solve the concave optimization problem.Simulations demonstrate the effectiveness of the proposed CR-SMEC-DHMA,surpassing the performance of current OMAenabled CRN,NOMA-enabled CRN,SMEC-OMA enabled CRN,and SMEC-NOMA enabled CRN methods,with ε-optimal results obtained at ε=10^(−3),while satisfying Performance Measures(PMs)including SME admission in SMEC,SME association with SrBS,SME-channel opportunistic allocation through spectrum sensing,sum rate and overall EE within the 6G CRN.
文摘Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the network.IPv6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration Scheme.IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications.Therefore,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of features.This paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential features.Moreover,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios.The results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)features.The proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.
基金supported by the Inner Mongolia Natural Science Fund Project(2019MS06013)Ordos Science and Technology Plan Project(2022YY041)Hunan Enterprise Science and Technology Commissioner Program(2021GK5042).
文摘6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques.
