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25 January 2021, Volume 42 Issue 1

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Papers

Construction method of attack scenario in cloud environment based on dynamic probabilistic attack graph

Wenjuan WANG, Xuehui DU, Dibin SHAN

2021, 42(1):  1-17.  doi:10.11959/j.issn.1000-436x.2021004

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Aiming at the problem of complex multi-step attack detection, the method of attack scenario construction oriented to cloud computing environment was studied.Firstly, a dynamic probabilistic attack graph model was constructed, and a probabilistic attack graph updating algorithm was designed to make it update periodically with the passage of time and space, so as to adapt to the elastic and dynamic cloud computing environment.Secondly, an attack intention inference algorithm and a maximum probability attack path inference algorithm were designed to solve the uncertain problems such as error and fracture of attack scenarios caused by false positive or false negative, and ensure the accuracy of attack scenario.Meanwhile, the attack scenario was dynamically evolved along with the dynamic probability attack graph to ensure the completeness and freshness of the attack scenario.Experimental results show that the proposed method can adapt to the elastic and dynamic cloud environment, restore the penetration process of attacker’s and reconstruct high-level attack scenario, and so provide certain references for building supervised and accountable cloud environment.

Joint intelligent optimization of task offloading and service caching for vehicular edge computing

Lei LIU, Chen CHEN, Jie FENG, Qingqi PEI, Ci HE, Zhibin DOU

2021, 42(1):  18-26.  doi:10.11959/j.issn.1000-436x.2021017

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Given the contradiction between limited network resources and massive user demands in Internet of vehicles, an intelligent vehicular edge computing network architecture was proposed to achieve the comprehensive cooperation and intelligent management of network resources.Based on this architecture, a joint optimization scheme of task offloading and service caching was furtherly devised, which formulated an optimization problem about how to offload tasks and allocate computation and cache resources.In view of the dynamics, randomness and time variation of vehicular networks, an asynchronous distributed reinforcement learning algorithm was employed to obtain the optimal task offloading and resource management policy.Simulation results demonstrate that the proposed algorithm achieves significant performance improvement in comparison with the other schemes.

Result aggregation algorithm based on differential evolution and Top-k ranking in learning Worker’s weight

Yuping XING, Yongzhao ZHAN

2021, 42(1):  27-36.  doi:10.11959/j.issn.1000-436x.2021010

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To solve the problem of quickly obtaining the optimal ranking result in the crowdsourcing result aggregation, an efficient and effective aggregation algorithm of Worker’s weight was proposed.The Worker’s weight optimization model based on differential evolution algorithm focused on the uncertainties and differences of Workers completing ranking tasks, the uncertainties and differences were reflected in the objective function and constraint conditions of the model.This model obtained the optimal weight of candidate results, and maximized the matching between Worker’s weight and result performance.Then, the optimization model solving method based on Top-k ranking was proposed to quickly obtain the optimal Worker’s weight with the appropriate k value for specific multi-data items ranking scenario.The optimization of Worker’s weight could realize optimized performance and speed of the result aggregation.The correctness of the algorithm is verified by qualitative analysis, the effectiveness and efficiency of the algorithm is verified by the simulation results, and the comparison with the relevant algorithms shows the optimal comprehensive performance of the algorithm.

Method against process control-flow hijacking based on mimic defense

Chuanxing PAN, Zheng ZHANG, Bolin MA, Yuan YAO, Xinsheng JI

2021, 42(1):  37-47.  doi:10.11959/j.issn.1000-436x.2021013

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To defeat the attack of process control flow hijacking, a threat model was established from the point of vulnerability utilization, and the fortress defense to cut off the key vulnerability utilization path was proposed.On the basis of studying the principle of mimic defense, a threat model of process mimic execution was proposed, and the threat model was analyzed and proved to be effective.Mimic execution could effectively cut off the attack path of control flow hijacking.The ptototype of mimic execution, MimicBox, was implemented.The validation experiment shows that MimicBox can effectively defend against most control flow hijacking attacks based on known binary vulnerabilities.The performance evaluation result shows that the overhead MimicBox lead to is less than 13% on CPU-intensive programs.The Comparative evaluation result shows that mimic execution is a more effective and practical active defense method compared with control flow integrity.

Large dynamic range microwave photonics mixing system based on parallel DPMZM

Yongsheng GAO, Fangjing SHI, Jiajun TAN, Yangyu FAN

2021, 42(1):  48-56.  doi:10.11959/j.issn.1000-436x.2021003

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To solve the problems of nonlinear distortion and limited dynamic range of microwave photonics mixing system, a large dynamic range microwave photonics mixing system based on parallel dual parallel Mach-Zehnder modulator (DPMZM) was proposed.The parallel modulation of radio frequency and local oscillator signals was realized by using DPMZM.The third-order intermodulation distortion (IMD3) in the output intermediate frequency signal was eliminated by configuring the electro-optic modulation index of the two parallel channels and the working point of the modulators.Finally, the dynamic range of the system was improved.Simulation results show that the proposed scheme can suppress IMD3 by 17.7 dB and increase the SFDR to $127.8\text{ dB}·{\text{Hz}}^{\frac{4}{5}}$ .

Blockchain-based service publishing scheme with recommendation for cold start users

Xuewen DONG, Haozhe LIU, Hui QIAO, Jiawei ZHENG

2021, 42(1):  57-66.  doi:10.11959/j.issn.1000-436x.2021032

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In order to solve the problem that the existing publishing systems were vulnerable to tampering, and it was difficult to recommend service information to “cold start” users, a blockchain-based service publishing scheme that supported cold-start user recommendations was proposed.The latent feature mapping model of a single auxiliary domain was extended to two auxiliary domains to make more accurate recommendations for cold start users in the target domain.In addition, the microservice architecture and block technology were combined to ensure system scalability, reliability and security.The experimental results of three real data sets extracted from Amazon transaction data show that the proposed recommendation model is better than most other recommendation methods, and the service release information can be safely stored in the blockchain to ensure that it is not changed.

Research on endogenous security data sharing mechanism of F-RAN for 6G

Yang LIU, Jun LI, Wenyun CHEN, Mugen PENG

2021, 42(1):  67-78.  doi:10.11959/j.issn.1000-436x.2021005

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In order to solve the data security problem of data sharing in the fog radio access network in the 6G mobile communication system, an endogenous secure data sharing mechanism that realized local differential privacy and dynamic batch auditing was proposed.First, the user ran the RAPPOR algorithm locally on the data to protect data privacy.Next, the fog access point cached and preprocessed the data.Then the high power node performed a data integrity audit based on the BLS signature and Merkle hash tree on the data cached on the fog access point.Finally, the BBU pool infered the original distribution of shared data through statistical analysis.Security analysis and simulation show that the proposed mechanism realizes the local differential privacy of users, supports secure multi-client batch audit and data dynamic operation, and has high efficiency in time, space and communication.

Short-term prediction method of oblique sounding ionosphere MUF based on robust Kalman filter

Guojun LI, Guangfa ZHENG, Changrong YE, Yinping ZHOU

2021, 42(1):  79-86.  doi:10.11959/j.issn.1000-436x.2021011

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To improve the low accuracy of ionospheric frequency forecasting, poor HF communication connectivity, and the severe impact of observational outliers in engineering on forecast accuracy, a short-term prediction method for oblique detection ionospheric MUF based on robust Kalman filtering was proposed.By studying the variation law of the measured MUF data and the causes as well as characteristics of observation errors, and exploiting the ionospheric reference model as a priori information, the state estimation equation of the Kalman filter model was improved.The cost function mechanism was introduced to realize the measurement update of the forecast state through Huber-M estimation, which reduced the influence of the observation outliers on the forecast results and improves the robustness of the proposed method.The simulation results show that the proposed method can effectively suppress the adverse effects caused by the observation outliers and has good robustness and stability.

YOLOv3-A: a traffic sign detection network based on attention mechanism

Fan GUO, Yongxiang ZHANG, Jin TANG, Weiqing LI

2021, 42(1):  87-99.  doi:10.11959/j.issn.1000-436x.2021031

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To solve the problem that the existing YOLOv3 algorithm had more false detections and missed detections for traffic sign detection task with small target problems and complex background, based on the YOLOv3, a channel attention method for target detection and a spatial attention method based on semantic segmentation guidance were proposed to form the YOLOv3-A (attention) algorithm.The detection features in the channel and spatial dimensions were recalibrated, allowing the network to focus and enhance the effective features, and suppress interference features, which greatly improved the detection performance.Experiments on the TT100K traffic sign data set show that the algorithm improves the detection performance of small targets, and the accuracy and recall rate of the YOLOv3 are improved by 1.9% and 2.8% respectively.

Research on Chinese predicate head recognition based on Highway-BiLSTM network

Ruizhang HUANG, Wenfan JIN, Yanping CHEN, Yongbin QIN, Qinghua ZHENG

2021, 42(1):  100-107.  doi:10.11959/j.issn.1000-436x.2021027

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Aiming at the problem of difficult recognition and uniqueness of Chinese predicate head, a Highway-BiLSTM model was proposed.Firstly, multi-layer BiLSTM networks were used to capture multi-granular semantic dependence in a sentence.Then, a Highway network was adopted to alleviate the problem of gradient disappearance.Finally, the output path was optimized by a constraint layer which was designed to guarantee the uniqueness of predicate head.The experimental results show that the proposed method effectively improves the performance of predicate head recognition.

Identity-based incremental signature scheme from lattices

Miaomiao TIAN, Jing CHEN, Hong ZHONG

2021, 42(1):  108-117.  doi:10.11959/j.issn.1000-436x.2021037

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By taking ideas of identity-based cryptography into incremental signatures, the concept of identity-based incremental signature was proposed, and then a specific scheme from lattices was also constructed.The scheme was shown to be provably secure against adaptive chosen identity and chosen message attacks in the standard model, assuming the hardness of the small integer solution problem.Theoretical analysis and experimental results show that the computational overhead of the incremental signature algorithm is less than that of the standard signature algorithm.

QoS aware evaluation model supporting service correlation in manufacturing cloud service composition

Xiaolan XIE, Lanying ZENG, Qinghai ZHAI

2021, 42(1):  118-129.  doi:10.11959/j.issn.1000-436x.2021021

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In order to select better quality of manufacturing cloud services that meet the demand of manufacture to complete manufacturing tasks in coordination, a QoS aware evaluation model supporting service correlation was proposed based on interface correlation, business entity correlation, and statistics correlation, aiming at the impact of QoS accuracy on combination screening.The cooperation time, KULC and IR parameters were introduced, and the historical information was used to predict and dynamically adjust the statistical association QoS changes to ensure timeliness.The feasibility of the proposed method is verified by an example analysis, and the experimental results show that the method can provide a more realistic solution for the service demander.

Comprehensive Reviews

Survey of the future network technology and trend

Tao HUANG, Jiang LIU, Shuo WANG, Chen ZHANG, Yunjie LIU

2021, 42(1):  130-150.  doi:10.11959/j.issn.1000-436x.2021006

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Several typical technologies about the future network were introduced.First, the background of each technology were introduced.Then, the current research progress and main results of each technology were expounded from eight aspects: network control and orchestration, programmable network, deterministic network, network computing and storage integration, network with artificial intelligence, network with blockchain, intelligent security network, space network.Finally the development trends and challenges of each technology were analyzed.It was expected that by 2030, the future network will support trillion-level, human-machine, all-time-space, safe, and intelligent connections and services.It is hoped that it can provide references and help for future network research.

Securing guarantee of the blockchain network:attacks and countermeasures

Peipei JIANG, Qian WANG, Yanjiao CHEN, Qi LI, Chao SHEN

2021, 42(1):  151-162.  doi:10.11959/j.issn.1000-436x.2021035

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While the security of blockchain has been the central concern of both academia and industry since the very start, new security threats continue to emerge, which poses great risks to the blockchain ecosystem.A systematic study was conducted on the most state-of-the-art research on potential security issues of blockchain.Specifically, a taxonomy was developed by considering the blockchain framework as a four-layer system, and the analysis on the most recent attacks against security loopholes in each layer was provided.Countermeasures that can strengthen the blockchain were also discussed by highlighting their fundamental ideas and comparing different solutions.Finally, the forefront of research and potential directions of blockchain security were put forward to encourage further studies on the security of blockchain.

Correspondences

Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network

Haining MENG, Xinyu TONG, Yuekai SHI, Lei ZHU, Kai FENG, Xinhong HEI

2021, 42(1):  163-171.  doi:10.11959/j.issn.1000-436x.2021015

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In view of the nonlinear, stochastic and sudden characteristics of operating environment of cloud server system, a software aging prediction method based on hybrid auto-regressive integrated moving average and recurrent neural network model (ARIMA-RNN) was proposed.Firstly, the ARIMA model performs software aging prediction of time series data in cloud server.Then the grey relation analysis method was used to calculate the correlation of the time series data to determine the input dimension of RNN model.Finally, the predicted value of ARIMA model and historical data were used as the input of RNN model for secondary aging prediction, which overcomes the limitation that ARIMA model has low prediction accuracy for time series data with large fluctuation.The experimental results show that the proposed ARIMA-RNN model has higher prediction accuracy than ARIMA model and RNN model, and has faster prediction convergence speed than RNN model.

High-speed transmission characteristics of nonlinear spectral broadening carrier in turbulent channel

Tianshu WANG, Ying ZHANG, Ce YU, Fang DONG, Wanzhuo MA, Xianzhu LIU

2021, 42(1):  172-177.  doi:10.11959/j.issn.1000-436x.2021014

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The nonlinear spectral broadening light source was used as a partially coherent carrier source with high repetition frequency to carry out experimental research on high-speed information transmission in atmospheric turbulence channels.A partially coherent beams source with nonlinear spectral broadening was obtained by pumping a highly nonlinear fiber with a picosecond fiber laser, and the repetition frequency could reach 10 GHz.The 10 Gbit/s pulse high-speed digital modulation was used and transmitted through a simulated atmospheric turbulence channel, the signal-to-noise ratio of the coherent optical carrier and partially coherent optical carrier before and after the turbulent channel transmission is reduced from 16.83 dB and 11.83 dB to 4.31 dB and 5.64 dB, respectively.In the simulated atmospheric turbulence channel at ?T=230℃, when the bit error rate is 3.8×10^-3, the sensitivity of partially coherent optical carrier links reaches-27.8 dBm, which is 1.6 dB higher than that of coherent optical carriers.