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25 March 2022, Volume 43 Issue 3

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Papers

Multi-dimensional time series anomaly detection method based on VAE-WGAN

Xueyuan DUAN, Yu FU, Kun WANG

2022, 43(3):  1-13.  doi:10.11959/j.issn.1000-436x.2022050

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As the deficiency of learning ability of traditional semi-supervised depth anomaly detection model to unbalanced multidimensional data distribution and the difficulty of model training, a multi-dimensional time series anomaly detection method based on VAE-WGAN architecture was proposed.VAE was used as a generator of WGAN.The Wasserstein distance was used as a measure between the model fitting distribution and the real distribution of the data to be measured, complex and high-dimensional data distributions could be learned.A sliding window was applied to divide the time series, the normal sequence data were used to train the model.According to the abnormal score of the waiting test sequence in the trained model, the anomaly was judged with adaptive threshold technology.The experimental results show that the model is easy to train and stable, and has obvious improvement over the existing generative anomaly detection model in accuracy, recall rate, F1 score and other anomaly detection performance indicators.

Provably secure quantum resistance two-server password-authenticated key exchange protocol

Anqi YIN, Yuanbo GUO, Ding WANG, Tongzhou QU, Lin CHEN

2022, 43(3):  14-29.  doi:10.11959/j.issn.1000-436x.2022052

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Aiming at the problem that the lattice-based single-sever password-authenticated key exchange (PAKE) protocols are not resistant to server compromise attack, while the existing lattice-based multi-server PAKE protocols are inefficient and incompatible with two-server scenarios.The first lattice-based two-party smooth projective hash function (SPHF) was proposed by utilizing the learning with errors (LWE), which was indistinguishability under adaptive chosen-ciphertext attack(IND-CCA2) secure.The parameters of the based public key encryption (PKE) scheme were also identified.On this basis, pertinent two-server PAKE protocols from lattices were designed countering both passive and active attackers.The two quantum resistance protocols were able to achieve password-only settings and the expensive cryptographic primitives were not used, including signature/verification, fully homomorphic encryption and secret sharing.The utilization of zero knowledge proofs were avoided by the protocol under the passive attackers.In the standard model, rigorous security proofs were provided for the two proposed protocols.Experimental results show that the proposed SPHF and PAKE protocols exhibit higher execution efficiency.

Optimization of reconfigurable SM2 algorithm over prime filed

Bin LI, Qinglei ZHOU, Xiaojie CHEN, Feng FENG

2022, 43(3):  30-41.  doi:10.11959/j.issn.1000-436x.2022043

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Aiming at the problems of inefficient of software, low utilization of hardware resources and poor scalability of SM2 algorithm, a reconfigurable optimization method of SM2 algorithm over prime filed was proposed.Through in-depth analysis of the SM2 algorithm, starting from different computation stages and characteristics, respectively using KOA fast multiplication, fast modular reduction and Barrett algorithm to achieve recommended or arbitrary parameters of the modular multiplication operation, and the radix-4 extended Euclidean algorithm was optimized and improved to accelerate the modular inverse operation.Then, in the standard projective coordinate system, the Montgomery method was used to improve the efficiency of point multiplication, and the data flow of point addition and double point was optimized to shorten the operation cycle to 12 clocks.At the same time, fast coordinate system conversion was realized inside the FPGA.Finally, the parallel scheduling management of multi-SM2 was designed and implemented to meet the computational requirements of multiple applications.The experimental results show that the optimized SM2 makes full use of FPGA resources and shortens the cycle of point multiplication.The maximum number of calculations per second is 352.48 times higher than the CPU (Intel i5-8300), which improves the performance and scalability.

Robust resource allocation algorithm for multicarrier NOMA security communication system

Yu ZHANG, Xiongwen ZHAO, Xiaoqing WANG, Suiyan GENG, Peng QIN, Zhenyu ZHOU

2022, 43(3):  42-52.  doi:10.11959/j.issn.1000-436x.2022044

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To improve the spectrum efficiency and enhance the information security of wireless network, a sum secrecy rate maximization-based robust resource allocation algorithm was proposed for a downlink multicarrier NOMA security communication system.Firstly, the artificial noise (AN) precoding vector was designed to be orthogonal to the legitimate channel, so that the legitimate transmission would not be affected by the AN.Then, considering the constraints of rate requirement of each user and the maximum transmit power of base station, a joint AN precoding, downlink data precoding and subcarrier allocation optimization problem was formulated under eavesdropping channel uncertainties.To solve that non-convex problem, it was decomposed into two joint optimization subproblems: precoding optimization and subcarrier allocation.The former was solved based on S-procedure and block coordinate descent (BCD) algorithm, the latter was solved by dynamic matching theory.Simulation results demonstrate that the proposed algorithm has good robustness and can effectively improve the sum secrecy rate.

Impossible differential cryptanalysis of Saturnin algorithm

Zilong JIANG, Chenhui JIN

2022, 43(3):  53-62.  doi:10.11959/j.issn.1000-436x.2022045

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A lightweight block cipher, Saturnin, is an AES-like algorithm.In a resource-constrained environment, Saturnin can also provide high security.The impossible differential analysis on Saturnin was proposed.First, based on the structure of Saturnin, the sufficient condition of 3.5-round impossible differential distinguisher of Saturnin was presented and proved, and 2^70.1truncated impossible differential distinguishers could be quickly constructed by utilizing the sufficient condition.Then, from the constructed 2^70.1distinguishers, the 64 distinguishers could be picked out pointedly and classified into four types.Four attack trails could be obtained by appending two rounds before the four types of distinguishers.These four attack trails had the same plaintext structure and a number of common subkey bits.With the help of these two properties, the complexity of the attack scheme could be reduced.Combined with the analysis technologies such as early abort, present the 5.5-round impossible differential attack scheme with 2^176.88chosen plaintexts, 2^143.88 256-bit blocks, and 2^176.915.5-round encryption.As so far, this is the known attack scheme for Saturnin against impossible differential attack.

Efficient strong privacy protection and transferable attribute-based ticket scheme

Huamin FENG, Rui SHI, Feng YUAN, Yanjun LI, Yang YANG

2022, 43(3):  63-75.  doi:10.11959/j.issn.1000-436x.2022053

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To solve the problems of efficiency, flexibility, and privacy protection faced by electronic tickets, an efficient and transferable attribute-based ticket scheme with strong privacy protection was proposed.Firstly, a ticket issuing algorithm based on attribute disclosure was constructed by combining attribute-based credentials and set commitment.Secondly, the structure-preserving signature on equivalence class and dynamic malleable signature were used to reduce the computational complexity of the ticket issuance, and the ticket transfer and ticket verification with constant complexity were realized.In addition, to prevent the possibility of malicious verifiers guessing user information according to the seller’s identity, the scheme not only realized the anonymity of the user, but also realized the anonymity of the seller in the ticket verification for the first time.Finally, the security definition of the scheme was given, and its security was reduced to either well-known complexity cryptography assumptions or the security of proven cryptography primitives.Comparison and experimental results demonstrate that the proposed scheme is flexible and efficient.

Composite Tor traffic features extraction method of webpage in actual network flow based on SDN

Hongping YAN, Qiang ZHOU, Shihao WANG, Wang YAO, Liukun HE, Liangmin WANG

2022, 43(3):  76-87.  doi:10.11959/j.issn.1000-436x.2022056

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Website fingerprinting (WF) methods for Tor webpage traffic are often based on the separated Tor traffic or even the separated Tor webpage traffic.However, distinguishing Tor traffic from the original traffic of the actual network and Tor webpage traffic from the Tor traffic costs amount of computation, which is more difficult than the WF attack itself.According to the current architecture of the Internet and the characteristics of network traffic converging to regional central nodes, the bi-directional statistical feature (BSF) was proposed for distinguishing Tor traffic through the intra-domain global perspective provided by the SDN structure of the central node and the node information disclosed by the Tor network.Furthermore, a hidden feature extraction method for Web traffic based on lifted structure fingerprinting (LSF) was proposed, and a composited Tor-webpage-identification traffic feature (CTTF) was proposed based on BSF and LSF deep features.For solving the problem of traffic training data scarcity, a traffic data augmentation method based on translation was proposed, which made the augmented traffic data as consistent as the Tor traffic data captured in the real working environment.The experimental results show that the identification rate based on CTTF can be improved by about 4% compared with using only the original data features.When there is less training data, the classification accuracy is improved more obvious after using the traffic data augmentation method, and the false positive rate can be effectively reduced.

Address overloading-based packet forwarding verification in SDN

Ping WU, Chaowen CHANG, Zhibin ZUO, Yingying MA

2022, 43(3):  88-100.  doi:10.11959/j.issn.1000-436x.2022047

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Aiming at the problem that the most existing forwarding verification mechanisms in software-defined network (SDN) verified packets hop-by-hop by incorporating new secure communication protocols, which incurred significant computation and communication overhead, an address overloading-based forwarding verification mechanism was proposed.The flow runtime was divided into consecutive random intervals by the ingress switch via overloading address fields of packet, basing on overloading address, packets were forwarded by each subsequent switch, and the controller sampled the packets forwarded by ingress and egress switch in the interval to detect abnormal behavior on the path.Finally, the proposed mechanism and simulation network was implemented and evaluated.Experiments show that the mechanism achieves efficient forwarding and effective anomaly detection with less than 8% of additional forwarding delays.

High-speed hardware architecture design and implementation of Ed25519 signature verification algorithm

Yiming XUE, Shurong LIU, Shuheng GUO, Yan LI, Cai’e HU

2022, 43(3):  101-112.  doi:10.11959/j.issn.1000-436x.2022061

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Aiming at the high performance requirements of signature verification for specific scenarios such as blockchain, a high-speed hardware architecture of Ed25519 was proposed.To reduce the number of calculations for point addition and point double, a multiple point multiplication algorithm based on interleaving NAF was conducted by using pre-computation and lookup tables.The modular multiplication operation was realized by using the Karatsuba multiplication and fast reduction method, and the point addition and point double operation was designed without modular addition and subtraction, which could effectively improve the performance of point addition and point double.Given that modular exponentiation was the most time-consuming operation in the decompression process, a new modular exponentiation approach was developed by parallelizing modular inverse and modular multiplication, and therefore the performance of the de-compression operation could be improved.The proposed architecture fully considers the use of resources and is implemented on the Zynq-7020 FPGA platform with 13 695 slices, achieving 8 347 verifications per second at 81.6 MHz.

Time hopping short reference carrier index differential chaos shift keying communication scheme

Hua YANG, Yu WANG, Siyuan XU, Guoping JIANG

2022, 43(3):  113-123.  doi:10.11959/j.issn.1000-436x.2022060

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In order to effectively utilize the transmission power of the reference signals in carrier index differential chaos shift keying (CI-DCSK), a novel time hopping short reference carrier index differential chaos shift keying communication system was proposed.Firstly, the symbol time was divided into multiple time slots, one of which was selected to send short reference signals according to the reference index bits.Then, analytical bit error rate expressions over additive white Gaussian noise and multipath Rayleigh fading channels were derived.Simulation results verify that the proposed scheme has a significant improvement in spectral efficiency, system energy efficiency and bit error rate performance.

Indoor EKF localization algorithm based on RFID carrier phase

Liangbo XIE, Xixi LIU, Yong WANG, Mu ZHOU, Zengshan TIAN

2022, 43(3):  124-134.  doi:10.11959/j.issn.1000-436x.2022048

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In order to solve the problem of low localization accuracy caused by indoor environment interference in the existing UHF RFID localization methods, an indoor extended Kalman filter (EKF) localization algorithm based on frequency hopping assisted RFID carrier phase was proposed.The virtual large bandwidth obtained by frequency hopping was used for rough distance estimation to realize multipath suppression, and the reliable dual frequency point selection and parameter optimization were completed through the phase after multipath suppression.Finally, EKF algorithm was used to realize high-precision and fast localization.Experimental results show that the average localization error of the proposed algorithm is 9.35 cm, and the real-time performance of the localization solution is nearly 10 times higher than the traditional integer solution method based on Chinese remainder theorem (CRT).

Energy efficiency optimization algorithm of heterogeneous networks based on hybrid energy supply and energy cooperation

Yang CAO, Ye ZHONG, Chunling PENG, Xiaofeng PENG

2022, 43(3):  135-147.  doi:10.11959/j.issn.1000-436x.2022042

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To reduce the base station energy consumption and co-channel interference in heterogeneous cellular networks, a joint optimization algorithm combined with energy harvesting and energy cooperation was proposed with the objective of energy efficiency optimization.First, a mixed-integer nonlinear programming problem for joint resource allocation was constructed considering the constraints of user service quality, the constraints of cellular base station power, and the constraints of renewable energy harvesting.Second, considering that the problem was an NP-hard problem which was difficult to solve directly, the complex original problem was decomposed into three subproblems, such as user association, power allocation, and energy cooperation, with the fixed-variable method, which were solved by using the Lagrangian pairwise method, particle swarm optimization algorithm, and matching theory, respectively.Finally, the final solution of the original problem was obtained by combining the above three algorithms through convergent iterative algorithms.The simulation results show that the proposed algorithm has improved convergence and system energy efficiency compared with the comparison algorithm.

Parallel division clustering algorithm based on Spark framework and ASPSO

Yimin MAO, Dejin GAN, Liefa LIAO, Zhigang CHEN

2022, 43(3):  148-163.  doi:10.11959/j.issn.1000-436x.2022054

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To deal with the problems that the partition clustering algorithm for processing massive data encountered problems such as large data dispersion coefficient and poor anti-interference, difficulty to determine the number of local clusters, local cluster centroids randomness, and low efficiency of local cluster parallelization and merging, a parallel partition clustering algorithm based on Spark framework and ASPSO (PDC-SFAS PSO) was proposed.Firstly, a meshing strategy was introduced to reduce the data dispersion coefficient of the data division and improve anti-interference.Secondly, to determine the number of clusters, meshing strategy based on potential function and Gaussian function were proposed, which formed an area with different sample points as the core clusters, and obtained the number of local clusters.Then, to avoid local cluster centroids randomness, ASPSO was proposed.Finally, a local cluster merging strategy based on cluster radius and neighbor nodes was introduced to merge clusters with large similarity based on the Spark parallel computing framework, which improved the efficiency of parallel merging of local clusters.Experimental results showed that the PDC-SFASPSO algorithm has good performance in data partitioning and clustering in a big data environment, and it was suitable for parallel clustering of large-scale data sets.

Recommendation model combining review’s feature and rating graph convolutional representation

Hailin FENG, Xiao ZHANG, Tongcun LIU

2022, 43(3):  164-171.  doi:10.11959/j.issn.1000-436x.2022049

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In order to fully exploit the effective information of the ratings and further investigate the importance of the review, a recommendation model combining review’s feature and rating graph convolutional representation was proposed.Graph convolutional neural network was used to learn the representation of user and item from the ratings data.Combining with text convolutional features, attention mechanism was utilized to distinguish the importance of the review.Finally, the representation learned from the review and the rating data was fused by the hidden factor model.The experimental results on Amazon’s public data showed that the proposed model significantly outperformed the traditional approaches, proving the effectiveness of the proposed model.

Systems resource allocation algorithm for RIS-assisted D2D secure communication based on parallel CNN

Zhengyu ZHU, Gengwang HOU, Chongwen HUANG, Gangcan SUN, Wanming HAO, Jing LIANG

2022, 43(3):  172-179.  doi:10.11959/j.issn.1000-436x.2022046

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To meet the requirements of intelligent signal processing and physical layer security, aiming at the shortage of spectrum resources, a resource allocation algorithm for reconfigurable intelligent surface (RIS)-assisted the device to device (D2D) communication was proposed.D2D users communicated by multiplexing the spectrum resources of cellular users.Considering the constraints of D2D transmission rate, base station transmission power and RIS transmission phase shift, the problem of maximizing user security rate was formulated.To solve the nonlinear programming problem, a parallel convolutional neural network (CNN) algorithm was proposed to obtain the optimal resource allocation scheme.Simulation results show that the parallel CNN algorithm can effectively improve the secrecy rate and it is significantly better than other benchmark algorithms.

Comprehensive Reviews

Auto-vectorization: recent development and prospect

Jingge FENG, Yeping HE, Qiuming TAO

2022, 43(3):  180-195.  doi:10.11959/j.issn.1000-436x.2022051

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The technology of SIMD is developing rapidly, and quite a few auto-vectorization methods have been proposed.Auto-vectorization can automatically translate scalar programs into vector programs based on SIMD extension, decrease workload of the programmers in coding vector programs, and effectively improve performance of programs.Based on that, the research achievements in the field of automatic vectorization in recent 10 years were analyzed and summarized.The key problems and major breakthroughs in automatic vectorization were classified from four aspects:semantic-maintaining analysis and transformation, vectorization grouping analysis and transformation, processor-oriented analysis and transformation, and performance evaluation analysis.Furtherly, the development trends and research directions of the four aspects were prospected.

Overview of anomaly detection techniques for industrial Internet of things

Haili SUN, Xiang LONG, Lansheng HAN, Yan HUANG, Qingbo LI

2022, 43(3):  196-210.  doi:10.11959/j.issn.1000-436x.2022032

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In view of the differences of existing anomaly detection methods and the applicability when applied to security protection of the industrial Internet of things (IIoT), based on technical principles, the network anomaly detection papers published from 2000 to 2021 were investigated and the security threats faced by IIoT were summarized.Then, network anomaly detection methods were classified into 9 classes and the characteristics of each class was studied.Through longitudinal comparison, the merits and shortcomings of different methods and their applicability to IIoT scenarios were sorted out.In addition, statistical analysis and comparison of common data sets were made, and the development trend in the future was forecasted from 4 directions.The analysis results can guide the selection of adaptive methods according to application scenarios, identify key problems to be solved, and point out the direction for subsequent research.

Correspondences

Generate medical synthetic data based on generative adversarial network

Xiayu XIANG, Jiahui WANG, Zirui WANG, Shaoming DUAN, Hezhong PAN, Rongfei ZHUANG, Peiyi HAN, Chuanyi LIU

2022, 43(3):  211-224.  doi:10.11959/j.issn.1000-436x.2022057

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Modeling the probability distribution of rows in structured electronic health records and generating realistic synthetic data is a non-trivial task.Tabular data usually contains discrete columns, and traditional encoding approaches may suffer from the curse of feature dimensionality.Poincaré Ball model was utilized to model the hierarchical structure of nominal variables and Gaussian copula-based generative adversarial network was employed to provide synthetic structured electronic health records.The generated training data are experimentally tested to achieve only 2% difference in utility from the original data yet ensure privacy.

Radio resource and trajectory optimization for UAV assisted communication based on user route

Lei LANG, Jingning WANG, Yi WANG, Zitao ZHAO

2022, 43(3):  225-232.  doi:10.11959/j.issn.1000-436x.2022059

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Recently, research on the application of unmanned aerial vehicle (UAV) in wireless communication networks has been widely studied.Aiming at the downlink wireless transmission system of UAV assisted mobile user communication, a method of resource allocation and trajectory optimization based on user route was proposed.According to the known user route, the estimated large-scale channel state information was obtained in advance, and a joint optimization problem of communication bandwidth allocation and trajectory optimization was established to maximize the minimum average rate of users.The problem was a nonconvex optimization problem, and there was nonlinear coupling between the variables.By introducing the method of alternating optimization of auxiliary variables and separated variables, the original problem was decomposed into two approximate convex optimization subproblems which could be solved, and the successive convex approximation was used to iteratively optimize the two subproblems, and an approximate suboptimal solution of the original nonconvex problem was obtained.Simulation results show that the proposed method of resource allocation and trajectory optimization can effectively improve the average data throughput of users, and improve the efficiency of UAV assisted communication on the premise of ensuring the communication quality of all users.

Executive dynamic scheduling algorithm based on high-order heterogeneity

Hongyong JIA, Yunfei PAN, Wenhe LIU, Junjie ZENG, Jianhui ZHANG

2022, 43(3):  233-245.  doi:10.11959/j.issn.1000-436x.2022055

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At present, most isomer scheduling models in DHR systems only considered second-order isomerism and lack dynamics.In order to solve these problems, a dynamic scheduling algorithm was proposed, which combined heterogeneity and dynamics by determining a scheduling scheme with maximum scheduling value.The value was obtained by combining high-order heterogeneity and historical information.The experimental results show that the proposed algorithm has better defense capabilities than other scheduling algorithms, and its strategy can achieve a balance of dynamics and security.