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25 February 2023, Volume 44 Issue 2

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Papers

Preventing flow table overflow against denial of service attack in software defined network

Dongbin WANG, Dongzhe WU, Hui ZHI, Kun GUO, Xu ZHANG, Jinqiao SHI, Yu ZHANG, Yueming LU

2023, 44(2):  1-11.  doi:10.11959/j.issn.1000-436x.2023036

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Aiming at denial of service attacks would cause overflow of the limited flow table space of the switch in software defined network, failure to install flow table rules for normal network packets, packet forwarding delay, and packet loss, FloodMitigation was proposed to prevent flow table overflow against denial of service attacks in software defined network.The management of the rate-limit flow rule installation based on available flow table space was adopted to limit the maximum installation speed of flow rules and the number of flow table space occupied by switch ports with denial-of-service attacks, and avoid flow table overflow.In addition, path selection based on available flow table space was adopted to balance flow table utilization of switches among multiple forwarding paths to avoid denial of service attacks on switches with less available flow table in the path.The experimental results demonstrate that FloodMitigation can effectively alleviate the harm of denial of service attacks in terms of preventing switch flow table overflow and packet loss, reducing resource consumption of controllers, and ensuring packet forwarding delay.

6G native intelligence network architecture enabled by intent abstraction and knowledge

Jingya YANG, Xiaogang TANG, Yiqing ZHOU, Ling LIU, Wang Jiangzhou

2023, 44(2):  12-26.  doi:10.11959/j.issn.1000-436x.2023016

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6G will evolve to an intelligent network, featured by native intelligence and openness.The study of standardization of intelligent network emphasizes the importance of intent-driven network for network intelligence.However, current intent-based networking takes the intent as “What to do” rather than “What you want”.Moreover, current knowledge defined network (KDN) can partially fulfill “How to configure the network” according to “What to do”.Therefore, a 6G native intelligent network architecture based on the intent abstraction and knowledge was proposed, aiming to achieve“How to configure the network” according to “What you want”.Firstly, an intent abstraction module was designed to obtain “What to do” from “What you want”, composed of intent acquisition, intent translation, intent mapping, and intent modeling.Secondly, the cognitive module was proposed to achieve “How to configure the network” according to “What to do”, which got network knowledge through joint optimization of machine learning and logical reasoning.Finally, enabling key technologies such as intent mapping, network information measurement, network policy generation, and network policy verification were introduced to support the implementation of 6G native intelligence.

Large-scale S-box design and analysis of SPS structure

Lan ZHANG, Liangsheng HE, Bin YU

2023, 44(2):  27-40.  doi:10.11959/j.issn.1000-436x.2023033

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A class of optimal linear transformation P over a finite field${\left(F_2^m\right)}^4$ was constructed based on cyclic shift and XOR operation.Using the idea of inverse proof of input-output relation of linear transformation for reference, a proof method was put forward that transformed the objective problem of optimal linear transformation into several theorems of progressive relation, which not only solved the proof of that kind of optimal linear transformation, but also was suitable for the proof of any linear transformation.By means of small-scale S-box and optimal cyclic shift-XOR linear transformation P, a large-scale S-box model with 2-round SPS structure was established, and a series of lightweight large-scale S-boxes with good cryptographic properties were designed.Only three kind of basic operations such as look-up table, cyclic shift and XOR were used in the proposed design scheme, which improved the linearity and difference uniformity of large-scale S-boxes.Theoretical proof and case analysis show that, compared with the existing large-scale S-box construction methods, the proposed large-scale S-box design scheme has lower computational cost and better cryptographic properties such as difference and linearity, which is suitable for the design of nonlinear permutation coding of lightweight cryptographic algorithms.

Joint estimation method of target number and orientation parameters for FDA-MIMO radar

Helin SUN, Hongyuan GAO, Yanan DU, Jianhua CHENG, Yapeng LIU

2023, 44(2):  41-51.  doi:10.11959/j.issn.1000-436x.2023037

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To address the problem that the frequency diverse array MIMO (FDA-MIMO) radar requires a priori information on the target number when locating multiple targets and the multidimensional parameter estimation consumes a large amount of computation, a joint estimation method was proposed.The angle and distance dependence of the FDA-MIMO were utilized to transform the estimation of target number and orientation parameters into a multimodal optimization problem on the spatial spectrum, and a density-based multimodal differential evolution algorithm was designed to solve it, which reduced the computational load and did not require a separate target number estimation algorithm.Simulation results show that the proposed method outperformed the existing methods in estimating the target number and orientation parameters.It overcomes the application limitations of the existing orientation parameter estimation methods and can obtain optimal estimation results without quantization error.

Sparse channel fast reconstruction algorithm for OFDM system based on IOC-CSMP

Wei CUI, Ying YU, Haixia YU, Chao CHEN, Yunpeng LI

2023, 44(2):  52-58.  doi:10.11959/j.issn.1000-436x.2023034

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A fast reconstruction algorithm based on inner product optimization and sparsity updating constraint was proposed for OFDM system channel estimation when the number of channel paths was unknown.By constructing and updating the selection vector, the inner product operation was reduced by using the atoms corresponding to the non-zero index of the selection vector.The atoms were optimized based on compressed sampling and backtracking strategies, and the channel estimation was completed by matching pursuit.The sparsity update and the stop condition for the algorithm was achieved by the energy difference between the two adjacent channel estimation so as to ensure fast convergence of the algorithm.The simulation results show that the proposed algorithm has better channel estimation performance than the least square algorithm, minimum mean square error algorithm, sparsity adaptive matching pursuit algorithm and adaptive regularized compressed sampling matching pursuit algorithm, and consumes less channel estimation time than the two adaptive methods.

Joint beam forming design for IRS-aided MIMO Internet of vehicles system

Lei ZHANG, Yu WANG, Jianjie TIAN, Lin ZHANG, Tianjiao ZHANG

2023, 44(2):  59-69.  doi:10.11959/j.issn.1000-436x.2023035

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A joint beamforming design method assisted by an IRS was proposed in MIMO Internet of vehicles system where the spectrum was shared by V2I and V2V users.Considering the constraints of V2V user’s data rate requirement, transmit power and IRS reflection phase shift, transmit precoding matrix at base station and reflective phase shift matrix of the IRS were jointly optimized to maximize channel capacity of the V2I user.The coupled non-convex optimization problem was decoupled and converted to be convex by using minimum mean square error, matrix analysis and inner approaching algorithm.An alternate iterative optimization algorithm was proposed to find the feasible solution.The performance comparisons of the proposed algorithm with several benchmarks were carried out and the impacts of the number of IRS reflective elements, IRS location and vehicle speed on spectrum efficiency were provided, respectively.The simulation results show that the proposed algorithm can converge quickly and the spectrum efficiency can be maximally improved by using the proposed method if the IRS is deployed near the base station.

Research on intrusion response strategy based on static Bayesian game in mobile edge computing network

Wei FAN, Cheng PENG, Dali ZHU, Yuqing WANG

2023, 44(2):  70-81.  doi:10.11959/j.issn.1000-436x.2023040

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In the mobile edge computing (MEC) environment, the resources of edge nodes are limited.It is difficult to detect the intrusion process accurately, and there is no effective intrusion response strategy to deal with external intrusions.An intrusion detection network structure suitable for mobile edge computing environment was proposed and an intrusion response decision model based on static Bayesian game was established to simulate the network interaction behavior between edge nodes and external intruders.The probability of attackers and defenders in the game process was predicted respectively.The influence of the system resource, the cost of intrusion response, the detection rate and false alarm rate were considered comprehensively by the intrusion response decision model.The response decision of the intrusion detection system was optimized on the basis of the considering both resource consumption of the intrusion detection and the privacy protection of the edge nodes.The factors that affected the decision-making of intrusion response were analyzed, and the experimental basis for the specific application was provided.

Algorithm of underdetermined convolutive blind source separation for high reverberation environment

Yuan XIE, Tao1 ZOU, Weijun SUN, Shengli XIE

2023, 44(2):  82-93.  doi:10.11959/j.issn.1000-436x.2023027

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To separate the underdetermined convolutive mixture signals in the high reverberation environment, a novel algorithm of underdetermined convolutive blind source separation was proposed.Aiming at the influence of high reverberation environment, a global impulse response network was designed to weaken reverberation echo, improving signal quality.A new mathematical model of time-frequency mixing signals was established based on the global impulse response network.The global impulse response matrix which shortened the length of the traditional impulse response, reduced the approximation error of model transformation caused by high reverberation.The real-time update learning rules of model parameters were designed based on the theory of nonnegative matrix factorization, and the source signal separation problem was converted into the model parameter optimization problem, achieving blind source separation of mixing signals.Experimental results show that the proposed algorithm can effectively realize the blind source separation of Chinese and English speech and music signals, and the comparision with existing popular algorithms verified the superiority of the proposed algorithm.

Anomaly detection model for multivariate time series based on stochastic Transformer

Weigang HUO, Rui LIANG, Yonghua LI

2023, 44(2):  94-103.  doi:10.11959/j.issn.1000-436x.2023042

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Aiming at the problem that the existing multivariate time series anomaly detection models based on variational autoencoders could not propagate long-term temporal dependencies between stochastic variables in latent space, the stochastic Transformer for MTS anomaly detection (ST-MTS-AD) model which combined Transformer encoder with VAE was proposed.In the inference network of the ST-MTS-AD, the MTS long-term temporal dependent features generated by Transformer encoder and the sampled values of the stochastic variables at the previous moment were inputted into the multilayer perceptron, the approximate posterior distribution of the stochastic variables at the current moment was generated by the multilayer perceptron, and the temporal dependencies between stochastic variables were realized.The gated transition function(GTF) was used to generate the prior distribution of stochastic variables.The generation network of the ST-MTS-AD reconstructed the distribution of the MTS values at each moment by the multilayer perceptron whose input was the MTS long-term temporal dependent features generated by the inference network and the approximate posterior sampling values of stochastic variables.The distribution of normal MTS dataset was learned by the variational inference technology, and the abnormal MTS segment was determined by the log-likelihood of the reconstruction probability.Experiments on four public datasets show that the ST-MTS-AD model significantly improves the F1 score over the typical baseline models.

OFDM transmission scheme with subcarrier supply index modulation

Yi GUO, Yiqing WANG, Yuanyuan FAN, Gang LIU

2023, 44(2):  104-111.  doi:10.11959/j.issn.1000-436x.2023030

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To address the drawback that subcarrier activation pattern (SAP) of the orthogonal frequency division multiplexing with index modulation (OFDM-IM) cannot match the binary numbers which affects the system performance, the orthogonal frequency division multiplexing with subcarrier supply index modulation (OFDM-SSIM) transmission scheme was proposed.The index utilization of the system was improved and the spectral efficiency (SE) of the system was enhanced by adding the supply index.Also, as the subcarrier activation pattern of the proposed scheme match the binary numbers, low complexity log-likelihood ratio (LLR) detection was made easy to adopt and bit error rate (BER) performance was maintained good.Theoretical analysis and simulation results show that the proposed scheme effectively improves the SE and BER performance over classical OFDM-IM scheme in additive white Gaussian noise (AWGN) channels and Rayleigh fading channels.

Wide area cooperative resource allocation algorithm for shortwave communication access network

Guojun LI, Xu HOU, Changrong YE, Yiping LUO

2023, 44(2):  112-121.  doi:10.11959/j.issn.1000-436x.2023014

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Aiming at the problem that short-wave point-to-point communication was not reliable enough to meet the actual needs, a wide area cooperative resource allocation algorithm based on shortwave communication access network was proposed.The reliability of the shortwave communication was improved by invoking multiple stations to coordinately guarantee users from different channels.The resource allocation problem was decomposed into two sub-problems of channel and station matching and station allocation.Firstly, the maximum expected success rate matching model was established to match the channel and the station, and the stations allocated to the channel were combined into different guarantee schemes.Then, the fuzzy analytic hierarchy process and the entropy weight method were used to obtain the subjective and objective scores of the scheme, and the optimal scheme was selected through fusion of evidence reasoning.The results show that the proposed algorithm can effectively improve the success rate of shortwave communication and has good adaptability.

Research on network attack analysis method based on attack graph of absorbing Markov chain

Haiyan KANG, Molan LONG

2023, 44(2):  122-135.  doi:10.11959/j.issn.1000-436x.2023002

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Existing intrusion path studies based on attack graph lack consideration of factors other than basic network environment information when calculating the state transition probability.In order to analyze the security of target network comprehensively and reasonably, a network attack analysis method based on attack graph of absorbing Markov chain was proposed.Firstly, a state transition probability normalization algorithm based on vulnerability life cycle was proposed based on attack graph.Secondly, the attack graph was mapped to the absorbing Markov chain and the state transition probability matrix was given.Finally, the state transition probability matrix was calculated to comprehensively analyze the node threat degree, attack path length and expected impact of the target network.The results show that the proposed method can effectively analyze the expected influence of node threat degree, attack path length and vulnerability life cycle on the whole network, which is helpful for security research personnel to better understand the security state of the network.

Improved Kalman filter indoor positioning algorithm based on CHAN

Rui JIANG, Yue YU, Youyun XU, Xiaoming WANG, Dapeng LI

2023, 44(2):  136-147.  doi:10.11959/j.issn.1000-436x.2023006

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Due to the raising complexity of the indoor environment, the influence of the non-line-of-sight error is gradually increasing in indoor positioning.How to reduce the non-line-of-sight error in the indoor positioning environment is particularly significant.The UWB indoor positioning technology was selected, Kalman filter has been used widely in reducing the positioning error in indoor non-line-of-sight situations.However, in the process of switching between line of sight and non-line-of-sight scenes, the Kalman filter will produce a new error.To solve this problem, an improved Kalman filter indoor positioning algorithm based on CHAN was proposed.The ranging results of five or more base stations were used to construct a positioning solution equation set.Then the CHAN algorithm that was sensitive to positioning errors under non-line-of-sight conditions was selected to calculate the result.Finally, residual processing was performed with the results of each base station and different confidence regions were judged in line with the residual processing.For different confidence regions, the Kalman filter preset gain factor K was used to improve the stability of the positioning result and reduce the positioning error in the conversion process.In the simulation environment, the error can reach about 80 cm.In real scene, the algorithm can reduce the positioning error in non-line-of-sight scenes to 60 cm, which can improve accuracy 60% higher than normal complex indoor positioning.

Research on multi-address time-based blockchain covert communication method

Dongyan HUANG, Kun LI

2023, 44(2):  148-159.  doi:10.11959/j.issn.1000-436x.2023026

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Aiming at the problem of low amount of information carried by the existing block timestamp interval hiding method, a multi-address time-based blockchain covert communication method was proposed.Firstly, the ciphertext was split and transmitted by different addresses.The content of the ciphertext fragment was represented by the block timestamp interval of the address.Then the interval of the blocks was read and counted by the receiver where these addresses were located.Finally, the ciphertext was restored by combination.In addition, in view of the lack of concealment measures in the time-based blockchain covert communication system, a method of adjusting the time interval of transaction initiation was proposed to reduce the probability of address specificity caused by covert communication behavior.The experimental results verify that the transmission rate of the proposed method is about n times higher than that of the time-based blockchain covert communication method when n addresses are involved.

Parallel algorithm for sensitive sequence recognition from long-read genome data with high error rate

Cheng ZHONG, Hui SUN

2023, 44(2):  160-171.  doi:10.11959/j.issn.1000-436x.2023009

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To solve the problem that existing algorithms were difficult to effectively identify sensitive sequences in genomic data for long-read with high error rate, a recognition algorithm using hybrid CPU and GPU parallel computing, called CGPU-F3SR, was proposed.Firstly, the long-read in genomic data were partitioned into multiple short-read, and the Bloom filtering mechanism was used to avoid repeated calculation of the short-read.Secondly, the k-mer coding strategy was used to extract in parallel the error information of all short-read, the recognition accuracy was promoted by improving the sequence similarity calculation model.Finally, CPU and GPU were used to coordinate and parallel to accelerate the calculation of short-read similarity to improve recognition efficiency.As a result, both two types of sensitive sequences including short tandem repeats and disease related sequences could be identified efficiently and accurately from genome data for long-read with high error rate.The experimental results of recognizing sensitive sequences from genomic data for long-read with length 100～400 kbp each show that, compared with existing parallel algorithm, the average recognition accuracy and precision rate of proposed CPU/GPU parallel algorithm CGPU-F3SR are increased by 7.77% and 43.07% respectively, its average false positive rate is reduced by 7.41%, and its average recognition throughput is increased by 2.44 times.

Optimal coalition structure generation strategy in multi-task concurrent edge computing environment

Shuxu ZHAO, Ping WEI, Xiaolong WANG

2023, 44(2):  172-184.  doi:10.11959/j.issn.1000-436x.2023012

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A discrete recent past-position updating strategy based m-ary discrete particle swarm optimization (MDPSO-DRPPUS) algorithm was proposed for the problem of large search space and low efficiency when solving the optimal coalition structure.First, the coalition structure with index-based was coded.Then, the multi-objective optimization problem was transformed into an eigenvalue function of the coalition structure.Finally, the optimal coalition structure was searched by using the MDPSO-DRPPUS algorithm.Experiments show that compared with the m-ary discrete particle swarm optimization (MDPSO) algorithm and genetic algorithm (GA), the proposed algorithm dramatically reduces the average running time, and improves the efficiency and equilibrium of the coalition structure and task completion efficiency of edge nodes.

Research on multi-UAV energy consumption optimization algorithm for cellular-connected network

Jingming XIA, Yufeng LIU, Ling TAN

2023, 44(2):  185-197.  doi:10.11959/j.issn.1000-436x.2023025

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In complex time-varying environment, the ground base station (GBS) may not assist the UAV.Therefore, a mobile edge computing (MEC) cellular-connected network based on digital twin (DT) technology was studied.Given the efficiency of multi-UAV, multiple high-altitude balloon (HAB) equipped with MEC servers were introduced.On this basis, an energy minimization problem for all UAV was proposed, and a multi-UAV trajectory optimization and resource allocation scheme was presented to solve it.The double deep Q-network (DDQN) was applied to handle the association between multi-UAV and multi-HAB, and the multi-UAV trajectory and computing resource allocation were jointly optimized by the successive convex approximation (SCA) and the block coordinate descent (BCD).Simulation experiments verify the feasibility and effectiveness of the proposed algorithm.The system energy consumption is reduced by 30%, better than the comparison algorithms.

Correspondences

AdaBoost algorithm based on target perturbation

Shufen ZHANG, Yanling DONG, Jingcheng XU, Haoshi WANG

2023, 44(2):  198-209.  doi:10.11959/j.issn.1000-436x.2023028

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Aiming at the problem that the multi-round iteration process in the AdaBoost algorithm will amplify the noise added to achieve differential privacy protection, which leads to slow model convergence and greatly reduced data availability, an AdaBoost algorithm based on target perturbation—DPAda was proposed.Target perturbation was used to add noise to sample weights, accurately calculated their sensitivity, and a dynamic privacy budget was given.In order to solve the problem of excessive noise superposition, three noise injection algorithms based on swing sequence, random response and improved random response were proposed.The experimental results show that compared with DPAda_Random and DPAda_Swing, DPAda_Improved achieves the privacy protection of data, has higher classification accuracy, as well as better than other differential privacy AdaBoost algorithm, and can also solve the problem of excessive noise caused by continuous noise addition.

Tripartite authenticated key exchange protocol for smart grid

Shengbao WANG, Xin ZHOU, Kang WEN, Bosen WENG

2023, 44(2):  210-218.  doi:10.11959/j.issn.1000-436x.20230369

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Most of the existing authentication schemes in the smart grid environment have the drawbacks of requiring manual participation or low performance, and thus do not meet the practical needs of smart grids.A new tripartite authenticated key exchange protocol was proposed for authentication and key establishment between three parties: smart meters, service providers and control center.The protocol was based on a physical unclonable function, which removed the drawback of requiring manual participation in the operation of the protocol.The security of the protocol was demonstrated by combining BAN logic and non-formal analysis methods.Comparing with similar representative protocols, the proposed protocol has better security and higher efficiency.

Research and optimization on the sensing algorithm for 6G integrated sensing and communication network

Xiaoyun WANG, Xiaozhou ZHANG, Liang MA, Yajuan WANG, Mengting LOU, Tao JIANG, Jing JIN, Qixing WANG, Guangyi LIU

2023, 44(2):  219-230.  doi:10.11959/j.issn.1000-436x.2023054

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High-precision sensing is one of the basic capabilities of 6G mobile communication system to fulfill the demands of many application scenarios in the future, and the integrated design of sensing and communication (ISAC) is an important direction of 6G research.The works on ISAC mainly focus on improving the sensing performance.However, besides high sensing accuracy, 6G ISAC network still has a high communication rate requirement.Therefore, joint analysis and design of communication and sensing is necessary.First, three classic sensing algorithms were introduced that could achieve multi-target ranging and speed measurement, and the algorithms were analyzed from three aspects: sensing accuracy, communication performance and computational complexity.It is shown that the optimal sensing accuracy, sensing capacity and communication rate could not be achieved at the same time by using either one algorithm.Second, combined with the characteristics of different sensing algorithms, an adaptive sensing algorithm was proposed that the receiver selected the appropriate sensing algorithm according to the measured receive signal-to-interference-plus-noise ratio to realize the joint optimization of sensing and communication performance.Finally, the link-level simulation was carried out to verify that the proposed algorithm can obtain better sensing accuracy and communication capacity than any single algorithm.