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25 August 2020, Volume 41 Issue 8

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Papers

Adaptive SDN switch migration mechanism based on coalitional game

Lan YAO,Julong LAN

2020, 41(8):  1-10.  doi:10.11959/j.issn.1000-436x.2020161

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The problem of poor control plane performance causes in software-defined Networking due to the unreasonable mapping relationship between controllers and switches.To address this issue,an adaptive switch migration mechanism based on coalitional game was proposed.First,comprehensively considering the controller resource utilization,control overhead,and flow establishment time,the switch migration problem was modeled as a combination optimization problem.Then,a game theory was introduced to design a distributed algorithm,where each controller ran control logic independently and implemented coalitional game between controllers to achieve an adaptive switch migration mechanism that adapted to traffic characteristics.The simulation results show that the proposed mechanism can better adapt to the flow characteristics,reduce the control traffic overhead by about 19% and the average flow settling time by 30%,and improve the controller resource utilization.

State recovery attack on ACORN v3 in nonce-reuse setting

Guoshuang ZHANG,Xiao CHEN,Dongdai LIN,Fengmei LIU

2020, 41(8):  11-21.  doi:10.11959/j.issn.1000-436x.2020164

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Based on differential-algebraic method and guess-and-determine technique,the state recovery attack of ACORN v3 was presented when one pair of key and Nonce was used to encrypt two messages.The time complexity of the attack was 2^122.5c,where c was the time complexity of solving linear equations.The data complexity and the storage complexity were negligible.Furthermore,according to the analysis on the sense of multiple nonce reuse,it is found that relatively complicated filter function of ACORN v3 makes it infeasible to extract the linear equations about the internal state directly from key streams.Thus,the risk of significantly reducing the attack complexity by increasing the times of nonce reuse can be effectively avoided.

Second fitness selection QPSO and SA cooperative search for large-scale discrete optimization algorithm

Zhaojuan ZHANG,Wanliang WANG,Jijun TANG

2020, 41(8):  22-31.  doi:10.11959/j.issn.1000-436x.2020173

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To address the large-scale discrete optimization problem,a cooperative optimization algorithm called IDQPSO-SA was proposed.First,a strategy by applying two selections on the averaging fitness values to update the mean best position was presented,which could overcome the deficiency that QPSO was not applicable for discrete problems.Second,the double cut joining (DCJ) sorting strategy was incorporated into IDQPSO-SA,since the DCJ sorting strategy could considerably reduce the search space.Finally,the probability jumping ability of simulated annealing (SA) was combined with the parallel search of QPSO,and the global search was carried out collaboratively.By comparing with existing algorithms,the experimental results show that IDQPSO-SA further improves the search efficiency and has a comparable performance when faced with large-scale discrete optimization problems.

Research on active defense based on multi-stage cyber deception game

Yongjin HU,Jun MA,Yuanbo GUO,Han ZHANG

2020, 41(8):  32-42.  doi:10.11959/j.issn.1000-436x.2020112

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In view of the characteristic that attacker depended on the detected information to decide the next actions,the non-cooperative signal game theory was applied to analyze cyber attack and defense.The signal deception mechanism in the process of cyber attack and defense was considered deeply by constructing a multi-stage cyber deception game model,and the dynamic analysis and deduction of the multi-stage cyber attack and defense was realized by considering the attenuation of cyber deception signals.A solution for multi-stage cyber deception game equilibrium was improved based on analysis of cyber attack and defense,and an optimal algorithm for selecting cyber deception defense strategies was designed.The effectiveness of the model is verified by simulations.The rules of multi-stage cyber deception games are summarized based on the results,which can provide effective guidance for the research on cyber active defense.

Sequential image deep learning-based Wi-Fi human activity recognition method

Qizhen ZHOU,Jianchun XING,Qiliang YANG,Deshuai HAN

2020, 41(8):  43-54.  doi:10.11959/j.issn.1000-436x.2020141

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For the problems existing in most of the researches,such as weak anti-noise ability,incompatible signal size and insufficient feature extraction of deep-learning-based Wi-Fi human activity recognition,a kind of sequential image deep learning-based recognition method was proposed.Based on the idea of sequential image deep learning,a series of image frames were reconstructed from time-varied Wi-Fi signal to ensure the consistency of input size.In addition,a low-rank decomposition method was innovatively designed to separate low-rank activity information merged in noises.Finally,a deep model combining temporal stream and spatial stream was proposed to automatically capture the spatiotemporal features from length-varied image sequences.The proposed method was extensively tested in WiAR dataset and self collected dataset.The experimental results show the proposed method could achieve the accuracy of 0.94 and 0.96,which indicate its high-accuracy performance and robustness in pervasive environments.

Research on data encryption system and technology for cloud storage

Peiyi HAN,Chuanyi LIU,Jiahui WANG,Shaoming DUAN,Hezhong PAN,Binxing FANG

2020, 41(8):  55-65.  doi:10.11959/j.issn.1000-436x.2020140

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To order to address the problem of cloud storage data security,the generic proxy-based data protection system was proposed,which could automatically and transparently secure sensitive data in browser-based cloud storage applications.A novel dynamic program analysis technique was adopted based on JavaScript API function hooking for automatically extending to various cloud applications.And a novel proxy executed searchable encryption solution was presented so that it could achieve data encryption while maintaining the original functions of cloud applications.Experimental results show that the system can support a variety of typical cloud services,effectively protect sensitive data,and bring a relatively low overhead.

Decision-aided-based multiple blind PN code estimation algorithm of asynchronous CDMA signal

Zhaoyang QIU,Tianyun LI,Xiangming CHEN

2020, 41(8):  66-78.  doi:10.11959/j.issn.1000-436x.2020163

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Aiming at the problem of blind estimation of multi-user pseudo-code of multi-path asynchronous code division multiple access (CDMA) signal,using the finite element (FA) characteristic of transmitted symbol,a decision aid (DA) method based on maximum likelihood was proposed.A two-step iterative estimation structure for PN code,transmitted bit and channel was designed to realize the estimation of multiple user code in asynchronous CDMA system with superior performance.Moreover,the Cramer-Rao bound (CRB) of PN code estimation in asynchronous CDMA signal was derived to evaluate the performance of proposed method.Simulation indicates significant improvement in performance which is close to the theory bound of the proposed method compared to commonly-used iterative least square with projection (ILSP) method.The method can also achieve superior estimation when the user number increases.

Resource optimization of secure energy efficiency based on mmWave massive MIMO-NOMA system with SWIPT

Fei ZHAO,Wanming HAO,Gangcan SUN,Yiqing ZHOU,Fei WANG,Yi WANG

2020, 41(8):  79-86.  doi:10.11959/j.issn.1000-436x.2020169

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The secure energy efficiency (SEE) problem was investigated for the millimeter wave (mmWave) multiple input multiple output (MIMO) non-orthogonal multiplex access (NOMA) systems with simultaneous wireless information and power transfer (SWIPT) in the presence of multiple legitimate receiver (LR) and an eavesdropper.LR was first grouped according to the channel state information and the cluster heads of each group were selected,then the LR of each cluster was served by each beam with NOMA and hybrid precoding technology.Based on this,a SEE maximization problem was formulated by optimizing power allocation and power splitting factors.The Dinkelbach algorithm and first order Taylor approximation were proposed to transform the original non-convex problem into a convex one,and an iterative algorithm was developed to solve it.Finally,numerical results show that the proposed scheme can effectively improve the SEE.

Evaluation method for autonomous communication and networking capability of UAV

Haitao ZHAO,Shishun GAO,Haijun WANG,Ting YONG,Jibo WEI

2020, 41(8):  87-98.  doi:10.11959/j.issn.1000-436x.2020143

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In order to accurately evaluate the autonomous communication and networking capability of these unmanned system which was instructive to the intelligent collaboration of UAV (unmanned aerial vehicle) system,the research of the UAV system which was adapted to the complex environment with countermeasure possibilities was focused on.The autonomous communication and networking capability of UAV system and their relationship from multiple perspectives was analyzed and modeled,including self-adaptation,self-decision,man-UAV interaction,cyber-physical integration and evolution,and an example was provided to illustrate the detailed evaluation process.The example results show that the proposed method comprehensively consider all the key aspects of the performance evaluation,which can be used to quantitatively evaluate the autonomous communication and networking capability of different UAVs or other unmanned systems.

Tensor-based approach to the co-prime planar array signal processing

Wei RAO,Yufeng GUI,Dan LI

2020, 41(8):  99-109.  doi:10.11959/j.issn.1000-436x.2020153

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For the co-prime planar array (CPPA) consisting of two sparse uniform rectangular array (URA),a new processing method based on tensor algebra was proposed to enhance the degrees of freedom (DoF).By dividing each URA into some overlapping subarrays,the received signals of two URAs were expressed as two tensors.And then the cross-correlation between such two tensors was processed into a received signal tensor of the virtual array.Analysis show that by the new method,the CPPA with 2 ²L -1 physical elements can be transformed into a virtual sparse non-uniform planar array with$\frac{{(L+1)}^4}{16}$elements.For the virtual array,the tensor decomposition-based approach for estimating the two-dimensional (2-D) direction of arrival (DoA) of the incident signal is also proposed,which means 2-D spectral peak searching is avoided.Compared with the co-prime planar signal processing methods reported in the literature,the proposed method can increase the DoF from L ²to$\frac{{(L+1)}^4}{16}+1$,and has the better performance of the 2-D DoA estimation and lower computational complexity.Simulation results demonstrate the efficiency of the proposed method.

Fault detection and diagnosis method for heterogeneous wireless network based on GAN

Xiaorong ZHU,Peipei ZHANG

2020, 41(8):  110-119.  doi:10.11959/j.issn.1000-436x.2020165

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Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.

Location based routing addressing mechanism of integrated satellite and terrestrial network

Hewu LI,Lixin LIU,Jun LIU,Qian WU

2020, 41(8):  120-129.  doi:10.11959/j.issn.1000-436x.2020135

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The ever-changing characteristics of the connection between the satellite network and the terrestrial network caused by the high-speed movement of the satellites have always been one of the most important problem that plagues the routing mechanism of the satellite network and integrated network.To address this problem,a location addressing based routing mechanism of integrated satellite and terrestrial network (LA-ISTN) was proposed.LA-ISTN exploited the user’s physical location in the user’s IP address to calculate the routing orientation.Based on the orientation,LA-ISTN could choose the best forward interface.Theoretical analysis and simulation experiments show that compared with snapshot protocol and OSPF routing protocol,LA-ISTN significantly reduces the route table storage overhead,with no routing updates cost caused by neighbor packet switching and communication.Inter-satellite route selection is not dependent on the prediction of link connection relations,with strong robustness,can always guarantee the network’s availability.

Local outlier factor algorithm based on correction of bidirectional neighbor

Xiaohui YANG,Xiaoming LIU

2020, 41(8):  130-140.  doi:10.11959/j.issn.1000-436x.2020119

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A local outlier factor algorithm based on bidirectional neighbor correction was proposed to solve the problems of existing outlier detection algorithms such as difficulty in parameter selection,poor efficiency and low accuracy.The bidirectional neighbor searching algorithm was used to reduce the neighbor search time.Then the bidirectional neighbor pruning algorithm was used to reduce the number of parameters and unnecessary calculations.And the correction factor based on bidirectional neighbors was used to improve the calculation accuracy.Experimental results show that the proposed algorithm has better performance in parameter selection and time efficiency than other outlier detection methods.The correction factor improves the accuracy of the algorithm,in the synthetic data set and UCI data set.

Optimization scheme for the SWIPT-NOMA opportunity cooperative system

Taoshen LI,Qianli NING,Zhe WANG

2020, 41(8):  141-154.  doi:10.11959/j.issn.1000-436x.2020109

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In order to improve the spectrum efficiency and performance of the simultaneous wireless information and power transfer (SWIPT) system,the non-orthogonal multiple access (NOMA) technology was introduced to construct the SWIPT-NOMA opportunistic relay system model.The fixed signal power allocation couldn’t adjust with other parameters of the system,and then affect the outage probability and resource utilization of the system.Therefore,a joint signal power and time allocation scheme was proposed to improve the system outage performance.In the proposed scheme,the expression of signal power distribution was obtained under the condition of satisfying the quality of service (QoS) rate of the node with poor channel state,and then the relation between the interruption probability and the time distribution of the system was deduced,the time allocation parameter was adjusted to affect the outage probability.The simulation results show that the constructed NOMA system has better outage performance than orthogonal multiple access (OMA) system,and the proposed joint signal power and time allocation outage scheme can effectively reduce the interruption probability of the system and improve the system performance.

CMDC:an iterative algorithm for complementary multi-view document clustering

Ruizhang HUANG,Ruina BAI,Yanping CHEN,Yongbin QIN,Xinyu CHENG,Youliang TIAN

2020, 41(8):  155-164.  doi:10.11959/j.issn.1000-436x.2020152

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In response to the problems traditional multi-view document clustering methods separate the multi-view document representation from the clustering process and ignore the complementary characteristics of multi-view document clustering,an iterative algorithm for complementary multi-view document clustering——CMDC was proposed,in which the multi-view document clustering process and the multi-view feature adjustment were conducted in a mutually unified manner.In CMDC algorithm,complementary text documents were selected from the clustering results to aid adjusting the contribution of view features via learning a local measurement metric of each document view.The complementary text document of the results among the dimensionality clusters was selected by CMDC,and used to promote the feature tuning of the clusters.The partition consistency of the multi-dimensional document clustering was solved by the measure consistency of the dimensions.Experimental results show that CMDC effectively improves multi-dimensional clustering performance.

Multi-scale aware dual path network for face detection in resource-constrained edge computing environment

Qi QI,Yingxin MA,Jingyu WANG,Haifeng SUN,Jianxin LIAO

2020, 41(8):  165-174.  doi:10.11959/j.issn.1000-436x.2020177

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Aiming at the problem that face detectors with complex deep neural structures are difficult to deploy in the resource-constrained edge computing environment,to reduce the resource consumption while maintain the accuracy in complex scenes such as multi-scale face changes,occlusion,blur,and illumination,SDPN(multi-scale aware dual path network) for face detection was proposed.The Face-ResNet (face residual neural network) was improved,and a dual path shallow feature extractor was used to understand the multi-scale information of the image through parallel branches.Then the deep and shallow feature fusion module,a combination of the underlying image information and the high-level semantic feature,was used in conjunction with the multi-scale awareness training strategy to supervise the multi-branch learning discriminating features.The experimental results show that SDPN can extract more diversified features,which effectively improve the accuracy and robustness of face detection while maintaining the efficiency of the model and low inference delay.

Multi-dimensional secure query scheme for fog-enhanced IIoT

Yousheng ZHOU,Chang TAN,Fei TANG

2020, 41(8):  175-186.  doi:10.11959/j.issn.1000-436x.2020127

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In view of the fact that most of the existing range query schemes for fog-enhanced IoT cannot achieve both multi-dimensional query and privacy protection,a privacy-preserving multi-dimensional secure query scheme for fog-enhanced IIoT was proposed.Firstly,the multiple ranges to be queried were mapped into a certain query matrix.Then,auxiliary vectors were constructed to decompose the query matrix,and then the auxiliary vector was processed by BGN homomorphic encryption to form a query trapdoor.Finally,with the homomorphic computation utilized by an IoT device terminal,the query trapdoor could be matched to its sensor data.Spatial complexity could be effectively reduced with the used specific auxiliary vectors.The confidentiality of sensor data could be ensured and the privacy of user’s query mode could be protected by the homomorphic encryption property.Experiments results show that the computational and communication costs are relatively low.

Comprehensive Review

Wireless ultra-reliable and low-latency communication:key design analysis and challenge

Yusun FU,Genke YANG

2020, 41(8):  187-203.  doi:10.11959/j.issn.1000-436x.2020154

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The current fragmented ultra reliable and low latency communication (URLLC) research focusing on a certain point was overcome.From the perspective of panoramic view,starting from the application scenarios and requirements,the system architecture,key technologies and solutions of URLLC were analyzed and introduced.Then,the physical layer detection performance requirements,link adaptation,radio resource management,end-to-end diversity solutions and how to integrate with TSN (time sensitive network) were analyzed in depth,and possible candidates were discussed.It hopes to have a thorough and comprehensive understanding of the theoretical research and application of URLLC,and a clear understanding of its challenges,so as to play a key reference for researchers and engineers in the related fields.

Correspondences

Electronic medical record data sharing scheme based on searchable encryption via consortium blockchain

Shufen NIU,Wenke LIU,Lixia CHEN,Caifen WANG,Xiaoni DU

2020, 41(8):  204-214.  doi:10.11959/j.issn.1000-436x.2020116

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Considering that it was difficult to share medical record data among different medical institutions in cloud storage,an electronic medical record data sharing scheme based on searchable encryption on blockchain was proposed.In order to realize the secure storage and sharing of electronic medical records in the scheme,the patient’s electronic medical record ciphertext was stored in the hospital server,the ciphertext hash value was stored in the private blockchain,and the keyword index was stored in the consortium blockchain.Searchable encryption was used to implement secure search of keywords in the consortium blockchain,and proxy re-encryption technology was used to realize the sharing of electronic medical records of patients by other data users.Security analysis shows that the proposed scheme can achieve ciphertext security and keyword security.Moreover,the performance of the scheme was analyzed by function analysis,computational efficiency analysis and numerical simulation.The performance analysis shows that the scheme can achieve high computational efficiency.

Construction of optimal zero correlation zone sequence set

Xiaoyu CHEN,Xichao GAO,Yongjie LI

2020, 41(8):  215-222.  doi:10.11959/j.issn.1000-436x.2020175

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The construction of zero correlation zone (ZCZ) sequence set was researched based on perfect sequences and orthogonal sequence set.With the method of constructing on finite field,the optimal zero correlation zone sequence sets were constructed,by changing the set O and R,multiple shift distinct ZCZ sequence sets could be obtained and the number of sets could be expended.Through the constructions,the length of ZCZ can be chosen flexibly to meet the requirements of different systems for channel delay under the condition of $p=\frac{Z}{N}$or$p^n=\frac{Z}{N}$,where p is a prime.