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25 June 2020, Volume 41 Issue 6

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Papers

UAV deployment and caching scheme based on user preference prediction

Jiazhi REN,Hui TIAN,Shaoshuai FAN,Yuanzhuo LIN,Gaofeng NIE,Jilong LI

2020, 41(6):  1-13.  doi:10.11959/j.issn.1000-436x.2020104

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In order to design an efficient edge caching policy considering spatial heterogeneity and temporal fluctuations of users’ content requests,a proactive caching scheme was proposed with UAV’s deployment location design based on user preference prediction.Firstly,each user’s preference characteristics were predicted based on file similarity and user similarity,and the request time and user location were also predicted when a content request occurs.Thereafter,on the basis of the predicted geographical location,request time and user preference,each UAV’s deployment location and the corresponding content placement were determined by virtue of clustering method based on SOM and AGNES.Simulation results show that the proposed scheme outperforms other three comparison schemes in terms of hit ratio and transmission delay.Furthermore,the results also reveal that content preference is correlated with different user features by different weights.Accordingly,different impact weights should be matched with different user features.

Provable security signcryption scheme based on RLWE without trapdoor

Zhen LIU,Yiliang HAN,Xiaoyuan YANG,Shuguang LIU

2020, 41(6):  14-25.  doi:10.11959/j.issn.1000-436x.2020093

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In view of the existing efficiency and security problems of lattice based signcryption,with the ABB16’s signature scheme ring-TESLA,a signcryption scheme without trapdoor named RLWE-SC was constructed,which achieved indistinguish ability against adaptive chosen cipher text attack (IND-CCA2) security and strongly existential unforgeability against chosen message attack (SUF-CMA) security respectively in terms of confidentiality and authentication based on the problem of learning with errors on ring.The size of the public and private keys was optimized by the construction on the ring.The complex trapdoor generation and preimage sample calculation was avoided by the structure without trapdoor.Efficiency analysis and experiment shows that RLWE-SC has better computational and communication performance than other similar lattice-based signcryption schemes with the same security strength.

Hierarchical game based spectrum access optimization for anti-jamming in UAV network

Chaoqiong FAN,Chenglin ZHAO,Bin LI

2020, 41(6):  26-33.  doi:10.11959/j.issn.1000-436x.2020114

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For the anti-jamming spectrum access optimization problem in unmanned aerial vehicle (UAV) communication networks,considering the complex and diverse malicious jamming from jammers,a Bayesian Stackelberg game was proposed to formulate the competitive relations between UAV users and jammers.Specifically,jammers acted as the leader,whereas users acted as followers of the proposed game.Based on their different utility functions,the jammer and users independently and selfishly selected their optimal strategies and obtained the optimal channels selection.Due to the NP-hard nature,it was challenging to obtain the Stackelberg Equilibrium of the proposed game.To this end,a hierarchical learning framework was formulated,and a hierarchical channel selection-learning algorithm was proposed.Simulations demonstrate that with the proposed hierarchical learning algorithm,UAV nodes can adjust their channel selection and obtain superior performance.

Theoretical limit of link prediction using a combination method

Yiteng WU,Hongtao YU,Ruiyang HUANG,Huawei LI

2020, 41(6):  34-50.  doi:10.11959/j.issn.1000-436x.2020125

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The problem that whether there a theoretical limit exists for link prediction combination methods and how to approximate was investigated.Link prediction methods were divided into single or combination methods,based on whether multidimension information was used,or whether the relation of multidimension information was defined directly.Limit theorems for link prediction by approximating a measurable function by a simple function sequence were provided.Combination rule and corresponding geometric interpretations and simulation examples for limit theorems were also provided.Limit theorems show why combination methods have higher accuracy and robustness than single methods.

Improved satellite resource allocation algorithm based on DRL and MOP

Pei ZHANG,Shuaijun LIU,Zhiguo MA,Xiaohui WANG,Junde SONG

2020, 41(6):  51-60.  doi:10.11959/j.issn.1000-436x.2020117

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In view of the multi-objective optimization (MOP) problem of sequential decision-making for resource allocations in multi-beam satellite systems,a deep reinforcement learning(DRL) based DRL-MOP algorithm was proposed to improve the system performance and user satisfaction degree.With considering the normalized weighted sum of spectrum efficiency,energy efficiency,and satisfaction index as the optimization goal,the dynamically changing system environments and user arrival model were built by the proposed algorithm,and the optimization of the accumulative performance in satellite systems based on DRL and MOP was realized.Simulation results show that the proposed algorithm can solve the MOP problem with rapid convergence ability and low complexity,and it is obviously superior to other algorithms in terms of system performance and user satisfaction optimization.

Secure obfuscation for encrypted threshold signatures

Yahong LI,Caifen WANG,Yulei ZHANG,Xiaodong YANG,Haiyan HUANG

2020, 41(6):  61-69.  doi:10.11959/j.issn.1000-436x.2020129

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Aiming at the key leakage security problem of the threshold signature,an encrypted threshold signature functionality was firstly proposed and securely obfuscated.The output of obfuscated circuit could be implemented by any third party without revealing the private key of threshold signature.Secondly,the security models of encrypted threshold signature functionality and the obfuscator were defined,such as the existential unforgeablity and the average case virtual black box property,and its correctness and security were proved.The analyses of theory and simulation experiment show that the obfuscation for encrypted threshold signature has feasibility.

Link prediction method based on matching degree of resource transmission for complex network

Shuxin LIU,Xing LI,Hongchang CHEN,Kai WANG

2020, 41(6):  70-79.  doi:10.11959/j.issn.1000-436x.2020124

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In order to solve the problem that many existing resource-transmission-based methods ignore the important influence of the matching degree of two endpoints on resource transmission,a link prediction method was proposed based on matching degree of resource transmission for complex networks.Firstly,by analyzing the two endpoints on the resource transmission path in detail,the method of quantifying the matching degree between two nodes was proposed.Then,in order to describe the influence of matching degree on resource transmission process between nodes,the matching degree of resource transmission was defined.Finally,based on the matching degree of resource transmission,a resource transmission matching index was proposed considering the resource amount of bidirectional transmission between nodes.The experimental results of nine datasets show that compared with other similarity indices,the proposed index can achieve higher prediction accuracy under the AUC and Precision metrics.

Mimic defense authentication method for physical access control

Qinglei ZHOU,Shaohuan BAN,Yingjie HAN,Feng FENG

2020, 41(6):  80-87.  doi:10.11959/j.issn.1000-436x.2020115

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To address the security problem of the vulnerability of the authentication methods of traditional physical access control systems,a mimic defense authentication method was designed based on the principle of mimic defense technique and its dynamic heterogeneous redundant architecture (DHR),using mobile 2D code as the interface and dynamic password as the core.First,the actuator pool of the authentication server was constructed.Then,a central controller consisting of functional modules such as input distribution agent,selector and voter was used to dynamically schedule heterogeneous redundant actuators from the actuator pool.Finally,a multimode ruling on the heterogeneous redundant actuator output to determine the authentication result was made by the voter.The experimental results show that the proposed authentication method has higher security and reliability compared to the traditional physical access control system authentication method,and at the same time,it can be used in combination with other authentication methods.

Method of unknown protocol classification based on autoencoder

Chunxiang GU,Weisen WU,Ya’nan SHI,Guangsong LI

2020, 41(6):  88-97.  doi:10.11959/j.issn.1000-436x.2020123

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Aiming at the problem that a large number of unknown protocols exist in the Internet,which makes it very difficult to manage and maintain the network security,a classification and identification method of unknown protocols was proposed.Combined with the autoencoder technology and the improved K-means clustering technology,the unknown protocol was classified and identified for the network traffic.The autoencoder was used to reduce dimensionality and select features of network traffic,clustering technology was used to classify the dimensionality reduction data unsupervised,and finally unsupervised recognition and classification of network traffic were realized.Experimental results show that the classification effect is better than the traditional K-means,DBSCAN,GMM algorithm,and has higher efficiency.

Threshold re-encryption based secure deduplication method for cloud data with resistance against side channel attack

Xin TANG,Linna ZHOU,Weijie SHAN,Dan LIU

2020, 41(6):  98-111.  doi:10.11959/j.issn.1000-436x.2020103

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For security and efficiency problems in threshold based deduplication for cloud data,a novel method based on threshold re-encryption was proposed to deal with side channel attacks.A lightweight threshold re-encryption mechanism was presented to transfer the secondary encryption to the cloud for execution and allow clients to generate ciphertext based on key segmentation instead of ciphertext segmentation,both of which largely reduce computational overhead of clients.Also,the proposed mechanism enables clients to decrypt from both one-time encrypted and re-encrypted ciphertext,thus avoiding the overhead of redundant encryption of the same file.Mutual integrity verification between cloud service provider and clients was also supported by the proposed method,which directly ensured the correctness of the correspondence between ciphertext and plaintext on client side.Experiments show that the proposed method not only largely reduces the computational overhead on client side,but also achieves superior storage performance on cloud side simultaneously.

Data center traffic scheduling strategy based on Fibonacci tree optimization algorithm

Yaomin WANG,Xia WANG,Yi DONG,Songhai ZHANG,Xinling SHI

2020, 41(6):  112-127.  doi:10.11959/j.issn.1000-436x.2020075

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To improve traffic scheduling capabilities in network provider data centers,both network structure and network traffic flow were considered at the same time.The analysis prediction and online scheduling mechanism was proposed in data center based on software defined networking (SDN).Aiming at the multi-dimensional,multi-constrained and multi-modal problems of traffic flow scheduling in data centers,the traffic flow scheduling strategy based on Fibonacci tree optimization (FTO) algorithm was proposed.FTO algorithm was embedded into two stages of analysis prediction and online scheduling,took it advantage of global local alternating and multi-model optimization characteristics,the optimal solution and suboptimal solutions of traffic scheduling had been got at one time.The emulator result shows that,the FTO traffic scheduling strategy can schedule traffic in data centers reasonably,which improves the load balancing capability of network providers' data centers effectively.

Intelligent detection method on network malicious traffic based on sample enhancement

Tieming CHEN,Chengqiang JIN,Mingqi LYU,Tiantian ZHU

2020, 41(6):  128-138.  doi:10.11959/j.issn.1000-436x.2020122

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To address the problem that the existing methods of network traffic anomaly detection not only need a large number of training sets,but also have poor generalization ability,an intelligent detection method on network malicious traffic based on sample enhancement was proposed.The key words were extracted from the training set and the sample of the training set was enhanced based on the strategy of key word avoidance,and the ability for the method to extract the text features from the training set was improved.The experimental results show that,the accuracy of network traffic anomaly detection model and cross dataset can be significantly improved by small training set.Compared with other methods,the proposed method can reduce the computational complexity and achieve better detection ability.

Design of key technologies for intranet dynamic gateway based on DPDK

Fucai CHEN,Weizhen HE,Guozhen CHENG,Shumin HUO,Dacheng ZHOU

2020, 41(6):  139-151.  doi:10.11959/j.issn.1000-436x.2020126

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Aiming at the problems of high packet processing delay and high overhead caused by IP hopping,active defense gateway system with multi-layer network deployment structure was designed and implemented based on the data plane development kit (DPDK).Firstly,based on the DPDK fast forwarding framework,forwarding and processing performance of the system were optimized.Secondly,for the dynamic random mapping gateway with three different types of IP addresses,an efficient IP address allocation algorithm and an unpredictable IP address conversion algorithm were designed.The experimental results show that the designed system can effectively reduce the rate of information acquisition of sniffing attack,while greatly improving the processing delay caused by dynamic hopping.

GAD:topology-aware time series anomaly detection

Qi QI,Runye SHEN,Jingyu WANG

2020, 41(6):  152-160.  doi:10.11959/j.issn.1000-436x.2020113

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To solve the problems of anomaly detection,intelligent operation,root cause analysis of node equipment in the network,a graph-based gated convolutional codec anomaly detection model was proposed for time series data such as link delay,network throughput,and device memory usage.Considering the real-time requirements of network scenarios and the impact of network topology connections on time series data,the time dimension features of time series were extracted in parallel based on gated convolution and the spatial dependencies were mined through graph convolution.After the encoder composed of the spatio-temporal feature extraction module encoded the original input time series data,the decoder composed of the convolution module was used to reconstruct the time series data.The residuals between the original data and the reconstructed data were further used to calculate the anomaly score and detect anomalies.Experiments on public data and simulation platforms show that the proposed model has higher recognition accuracy than the current time series anomaly detection benchmark algorithm.

Comprehensive Review

Survey of the intelligent and connected vehicle cybersecurity

Wufei WU,Renfa LI,Gang ZENG,Yong XIE,Guoqi XIE

2020, 41(6):  161-174.  doi:10.11959/j.issn.1000-436x.2020130

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Cyber attacks on vehicles not only cause privacy leaks and economic losses but also endanger human life and even rise to national public safety issues.Therefore,the research on the cybersecurity of intelligent and connected vehicle (ICV) has become a research hot spot.Firstly,the structural status and characteristics of the in-vehicle network (IVN) in ICV were introduced,and the challenges and constraints of cybersecurity enhancement design for IVN were also presented.Secondly,focusing on the current functional safety and cybersecurity issues of IVN,a survey of the current cybersecurity enhancement researches for IVN was conducted.Finally,according to the characteristics of the IVN structure,some important research directions and suggestions about cybersecurity problems of ICV were pointed out from the three aspects of standard construction,functional safety and cybersecurity.

Correspondences

Research on pedestrian trajectory prediction method based on social attention mechanism

Linhui LI,Bin ZHOU,Jing LIAN,Yafu ZHOU

2020, 41(6):  175-183.  doi:10.11959/j.issn.1000-436x.2020100

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In order to improve the speed,accuracy and model interpretability of trajectory prediction in pedestrian interaction,a GAN model based on social attention mechanism was proposed.Firstly,a new type of social relationship on pedestrians was defined to model social relationships and a network model based on the attention mechanism was designed to improve the speed and interpretability of network prediction.Secondly,the influence of different pooling mechanisms on the prediction results was explored to determine the pooling model with excellent performance.Finally,a trajectory prediction network was built on this basis and trained on the UCY and ETH data sets.The experimental results show that the model not only has better prediction accuracy than the existing methods,but also improves the real-time performance by 18.3% compared with the existing methods.

Multi-tenant virtual domain isolation construction method based on L-DHT

Lifeng CAO,Xin LU,Zhensheng GAO,Xuehui DU

2020, 41(6):  184-201.  doi:10.11959/j.issn.1000-436x.2020088

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Aiming at the problem of security isolation of multi-tenant data in cloud environment,a tenant virtual domain isolation construction method based on L-DHT was proposed.Firstly,through the design of multi-tenant isolation mapping algorithm based on label-hash mapping,the balanced mapping mechanism of tenant resources was constructed to realize the distributed management of tenant resources.Secondly,for the security isolation and access between tenant data mapped to the same storage node,based on the predicate encryption mechanism,through the effective binding of security labels and tenant data,a tenant data isolation storage algorithm based on label predicate encryption was designed.Finally,by the design of multi-dimensional tenant data isolation control rules and using the analysis and authentication of security labels,independent,logical and secure virtual domains between tenants were built hierarchically.The security analysis shows that the method constructs tenant virtual domains which are secure and non-interference with each other.The simulation results show that the mapping algorithm can achieve a better dynamic load balance.The efficiency and security of data access are verified by the comparative analysis of tenant data retrieval efficiency and authentication access security.

Novel unified chaotic system with multi-parameter invariable Lyapunov exponent spectrum

Qiuzhen WAN,Zhaoteng ZHOU

2020, 41(6):  202-213.  doi:10.11959/j.issn.1000-436x.2020080

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Based on the traditional Qi chaotic system,a novel unified chaotic system with the complex chaotic characteristics was constructed by adding the control parameters and modifying the nonlinear terms.Firstly,basic dynamical characteristics of chaotic system were analyzed,and phase portrait,time domain waveform diagram,Poincare mapping and power spectrum diagram were numerically simulated.Secondly,system parameters influence on chaotic system was discussed through Lyapunov exponent spectrum,bifurcation diagrams and chaotic signal amplitude.It was found that the unified chaotic system can generate the four new types of two-wing chaotic attractors with the multi-parameter invariable Lyapunov exponent spectrum characteristics.Meanwhile,there exist the functions of the global and local nonlinear amplitude modulation parameters.Thirdly,taking the first chaotic attractor of system as an example by introducing the two new types of nonlinear functions,the expansion of grid multi-wing attractor was realized.Finally,the hardware circuit of novel unified chaotic system was constructed.The four new types of chaotic attractors are observed experimentally,which is consistent with numerical simulation results and verified the feasibility of the proposed system.