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25 May 2022, Volume 43 Issue 5

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Papers

Privacy-protected crowd-sensed data trading algorithm

Yong ZHANG, Dandan LI, Lu HAN, Xiaohong HUANG

2022, 43(5):  1-13.  doi:10.11959/j.issn.1000-436x.2022082

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To solve the problem that data privacy leakage of participants under the crowd-sensed data trading model, a privacy-protected crowd-sensed data trading algorithm was proposed.Firstly, to achieve the privacy protection of participants, an aggregation scheme based on differential privacy was designed.Participants were no longer needed to upload raw data, but analyzed and calculated the collected data according to the task requirements, and then sent the analysis results to the platform after adding noise in accordance with the privacy budget allocated by the platform to protect their privacy.Secondly, in order to ensure the credibility of participants, a reputation model of participants was proposed.Finally, in order to encourage consumers and participants to participate in transactions, a data trading optimization model was constructed by considering the consumer’s constraint on the result deviation，the participant’s privacy leakage compensation and platform profit, and a POA based on genetic algorithm was proposed to solve the model.The simulation results show that the POA not only protects the privacy of participants, but also increases the profit of the platform by 29.27% and 20.45% compared to VENUS and DPDT, respectively.

Research on BER performance of the OAM-SK FSO communication system with wavefront phase correction

Shuang LI, Ping WANG, Tao LIU, Yuting PAN, Wei WANG

2022, 43(5):  14-23.  doi:10.11959/j.issn.1000-436x.2022110

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On the basis of Gerchberg-Saxton (GS) algorithm and angular-spectrum theory, an improved wavefront phase correction algorithm to the Laguerre-Gaussian (LG) beams was proposed for the orbital angular momentum-shift keying (OAM-SK) modulation-based free space optical (FSO) communication system under weak atmospheric turbulence.The light field distributions of the probe beam at transmitter and receiver were regarded as the input of the improved wavefront phase correction algorithm.And the correction phase mask was iteratively calculated to correct the distorted LG beams, thereby alleviating the inter-model crosstalk caused by atmospheric turbulence.Simulation results show that the improved wavefront phase correction algorithm is superior to the conditional GS algorithm.And with the increase of the refractive-index structure parameter, the bit error rate (BER) performance of the OAM-SK FSO communication system is significantly improved.

Fast loop-free path migration strategy in software defined network

Binghao YAN, Qinrang LIU, Jianliang SHEN, Xiantuo TANG, Dong LIANG

2022, 43(5):  24-35.  doi:10.11959/j.issn.1000-436x.2022088

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Aiming at the problems of slow and faulty path migration caused by distributed deployment and asynchronous operation of data plane forwarding devices in software defined network, a fast loop-free path migration strategy was proposed.First, a fast loop detection algorithm based on node ranking was proposed.By comparing the position differences of adjacent nodes on the old and new paths of the flow, whether there was a forwarding loop in the path migration process and the location detection where the loop occurs could be quickly determined.Then, a greedy update mechanism based on node relaxation dependency was proposed.The fast loop detection algorithm was used to uncover the relaxation dependency between the common switches on the old and new paths, and the number of switches updated in each round of the migration process was ensured to be maximized.Simulation results show that the proposed strategy can effectively avoid migration loops and obtain the optimal update time overhead under different network states compared with existing migration schemes.

High spectral efficiency SSB-PAM-DD scheme with high linewidth tolerance

Dongxu LU, Xian ZHOU, Fei LIU, Jiahao HUO, Jinhui YUAN, Keping LONG

2022, 43(5):  36-44.  doi:10.11959/j.issn.1000-436x.2022100

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For low-cost and high chromatic dispersion (CD) robustness single sideband (SSB) with direct detection (DD), three schemes of SSB with pulse amplitude modulation (PAM) were investigated.Among that, the highest spectral efficiency was achieved by the scheme of adding the frequency down-conversion at the transmitter.However, that scheme reduces the tolerance for laser linewidth.Hence, based on the character of the SSB-PAM signal, a DSP scheme was proposed, including a modified equalization algorithm with phase distortion immunity and blind phase search algorithm.The simulation results show that the modified scheme can tolerate 1 MHz linewidth for 112 Gbit/s SSB-PAM-DD, while the original scheme for SSB-PAM was only 100 kHz at the same bit error rate (BER) threshold.Therefore, the proposed scheme can achieve a high frequency efficiency, high linewidth tolerance, and low-cost SSB-PAM signaling transmission.

Papers

Research on meaningful image encryption algorithm based on 2-dimensional compressive sensing

Hua REN, Shaozhang NIU, Ruyong REN, Zhen YUE

2022, 43(5):  45-57.  doi:10.11959/j.issn.1000-436x.2022101

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Aiming at the problems that the existing compressive sensing-based meaningful image encryption algorithms have low visual security of the encrypted images and poor quality of the reconstructed images, a 2-dimensional compressive sensing-based (2DCS) meaningful image encryption algorithm was proposed.Firstly, a chaotic pseudo-random sequence generation method associated with plaintext was designed, and the global random permutation and grayscale transformation operations were used for pre-encryption to improve the decrypted image quality.The generated pre-encrypted image was used as the input for 2DCS, and the secret image was generated after the compression encryption and quantization operations.Secondly, the relationship between the hidden and the modified data was considered, and an adaptive embedding method was adopted to modify the carrier coefficient values to improve the visual security of meaningful encrypted image.Finally, the 2-dimensional projection gradient reconstruction method was adopted to decompress and decrypt to obtain the decrypted image.The experimental results show that, compared with the existing algorithms, the proposed algorithm not only improves the visual security of encrypted image and the quality of reconstructed image, but also can resist noise and cropping attacks.

Efficient and provably-secure certificateless sequential aggregate signature scheme

Zhu WANG, Siqi YANG, Fenghua LI, Kui GENG, Tingting PENG, Mengyao SHI

2022, 43(5):  58-67.  doi:10.11959/j.issn.1000-436x.2022073

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Aiming at the problem that current schemes mostly let the latter signer to verify the multiple signatures of the previous signer, and the message is signed and then passed to the next signer, leading to the efficiency problem of long overall signature time.A sequential aggregate signature scheme based on bilinear pairs was proposed.The aggregate signatures of documents were generated by multiple users in a certain order, and only the final signature was needed to be verified to confirm the correct order of signatures and the legitimacy of multiple user signatures.The complexity of verifying the multi-user sequential signature was effectively reduced and the offline verification of the authenticity of signature was realized when the user was offline or in a delay-tolerant network with limited node caching capacity and network resources.It is shown that the proposed scheme is existential unforgeability against chosen-message attacks under adversary adaptive selection messages in the random oracle model.

DDAC: a feature extraction method for model of image steganalysis based on convolutional neural network

Xiaodan WANG, Jingtai LI, Yafei SONG

2022, 43(5):  68-81.  doi:10.11959/j.issn.1000-436x.2022089

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To solve the problem that for image steganalysis based on convolution neural network, manual designed filter kernels were used to extract residual characteristics, but in practice, these kernels filter were not suitable for each steganography algorithm and have worse performance in application, a directional difference adaptive combination (DDAC) method was proposed.Firstly, the difference was calculated between center pixel and each directional pixel around, and 1 × 1 convolution was adopted to achieve linear combinations of directional difference.Since the combination parameters self-adaptively update according to loss function, filter kernels could be more effective in extracting diverse residual characteristics of embedding information.Secondly, truncated linear unit (TLU) was applied to raise the ratio of embedding information residual to image information residual.The model’s coveragence was accelerated and the ability of feature extraction was promoted.Experimental results indicate that substituting the proposed method could improve the accuracy of Ye-net and Yedroudj-net by 1.30%~8.21% in WOW and S-UNIWARD datasets.Compared with fix and adjustable SRM filter kernels methods, the accuracy of test model using DDAC increases 0.60%~20.72% in various datasets, and the training progress was more stable.DDAC-net was proved to be more effective in comparsion with other steganalysis model.

Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network

Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

2022, 43(5):  82-91.  doi:10.11959/j.issn.1000-436x.2022078

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For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.

Dynamic generalized principal component analysis with applications to fault subspace modeling

Xiaofeng FENG, Jianfeng XU, Chuan HE

2022, 43(5):  92-101.  doi:10.11959/j.issn.1000-436x.2022091

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In order to solve the problem of inaccurate modeling of fault subspace, traditional fault subspace modeling method did not consider the fact that fault data contain both normal and fault condition information, or did not consider the dynamic factors in the fault data, these flaws may lead to the case that the fault subspace cannot be extracted accurately, a dynamic generalized principal component analysis (DGPCA) method was proposed.By reorganizing the lagged input data, the dynamic characteristics between normal and fault data were extracted by the proposed DGPCA method, and then the fault subspaces could be modeled for further fault diagnosis.Finally, simulation results confirm the availability of the proposed method for fault subspace modeling and fault diagnosis.

Research on reflection characteristics of the terahertz channel for 6G

Pan TANG, Jiaxin LIN, Jianhua ZHANG, Lei TIAN, Zhaowei CHANG, Liang XIA, Qixing WANG

2022, 43(5):  102-109.  doi:10.11959/j.issn.1000-436x.2022102

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The reflection characteristics of the terahertz channel are crucial for understanding and mastering the propagation mechanism of the terahertz channel, which are also required for a high-precision terahertz channel model for 6G.Therefore, the research status of terahertz channel reflection characteristics in theoretical modeling and measurement analysis were first summarized.Then, the reflection coefficient measurement campaign in the frequency range of 240 GHz to 310 GHz for five kinds of common building materials was conducted by a time-domain correlation-based terahertz channel measurement platform.It was found that the reflection coefficients were related to the incident angle.Based on the Rayleigh reflection coefficient theoretical model, a statistical reflection coefficient model was further proposed as a function of incident angle.Generally, the proposed model could accurately describe the variation law of the reflection coefficient with angle.Finally, research directions of terahertz channel reflection characteristics were discussed.

Lightweight searchable medical data sharing scheme

Xinchun YIN, Mengyu WANG, Jianting NING

2022, 43(5):  110-122.  doi:10.11959/j.issn.1000-436x.2022090

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The attribute-based encryption scheme supporting policy hiding and keyword search had a good application prospect in medical scenarios.However, most of the existing schemes did not support large attribute university or adopt the ＆quot;AND gate＆quot; structure, which limited their scalability and flexibility of access control, and many schemes could not resist offline dictionary guessing attacks.In addition, attribute-based encryption involved a large number of bilinear pairing operations, which was inconvenient for user equipment with limited computing resources.A lightweight searchable medical data sharing scheme was proposed.Based on the support for keyword search and policy hiding, a large attribute university and a linear secret sharing structure were adopted to improve the scalability and flexibility of access control.The Intel SGX was used to re-encrypt data to achieve anti-offline dictionary guessing attack.The computational overhead of decryption was reduced to a constant level, which was suitable for user equipment with limited computing resources.Finally, it is proved that the proposed scheme has the security of selecting plaintext indistinguishable and can resist offline dictionary guessing attacks.

Efficient dynamic searchable encryption scheme for conjunctive queries based on bidirectional index

Ruizhong DU, Yuqing ZHANG, Mingyue LI

2022, 43(5):  123-132.  doi:10.11959/j.issn.1000-436x.2022099

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To solve the problems of complicated operation, information leakage, and inflexible query method in the update process of existing dynamic searchable encryption scheme, an efficient dynamic searchable encryption scheme (named BPC-DSSE) for conjunctive query with forward and backward privacy was proposed.A bitmap index was used to construct a bidirectional index structure to simplify the dynamic update process, and the access pattern was hidden through symmetric encryption with homomorphic addition.At the same time, since the addition and deletion operations were completed by modulo addition, the leakage of the update process could be reduced by hiding the update type.Security analysis shows that the BPC-DSSE scheme achieves forward and Type-I^- backward privacy.The simulation results show that the BPC-DSSE scheme has higher update and retrieval efficiency than other conjunctive query schemes.

Hybrid tabu search algorithm for excellent Boolean function

Weiqiong WANG, Haojie XU, Meng CUI, Qiong XIE

2022, 43(5):  133-143.  doi:10.11959/j.issn.1000-436x.2022096

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Boolean function in symmetric cryptographic algorithm must satisfy excellent cryptographic criteria to ensure the security of the algorithm.By combining the advantages of tabu search algorithm and hill climbing algorithm, a new heuristic generation algorithm called hybrid tabu search algorithm for excellent Boolean function was proposed.A large number of Boolean function with high nonlinearity, low autocorrelation, one-resilient, optimal algebraic degree, optimal algebraic immunity, optimal (suboptimal) resistance to fast algebraic attacks could be obtained quickly by applying the proposed algorithm.Simulation results demonstrate that the cryptographic properties of the Boolean function obtained by the proposed algorithm with strong search ability and fast running speed are better than the results of known optimization algorithm.Moreover, the algorithm also provides good Boolean function that cannot be obtained by using construction method.

Certificateless ciphertext retrieval scheme with multi-user and multi-keyword based on cloud-edge collaboration

Xiaodong YANG, Tian TIAN, Jiaqi WANG, Meijuan LI, Caifen WANG

2022, 43(5):  144-154.  doi:10.11959/j.issn.1000-436x.2022104

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To solve the problems of single-user search, single-keyword search, high computational cost and low-security level of ciphertext data retrieval in the industrial Internet of things environment, a certificateless ciphertext retrieval scheme with multi-user and multi-keyword based on cloud-edge collaboration was proposed.A user access permissions table was set and once encryption algorithm was executed to realize multi-user search and update users’ access permissions.A cloud-side collaborative computing model was introduced to match keyword ciphertext and keyword trapdoor efficiently by a linear scanning method when the keyword ciphertext does not entirely contain the search keyword.Key escrow and certificate management problems were solved by utilizing certificateless encryption system.Keyword ciphertext authentication was ensured by using digital signature technology.The security analysis results show that the proposed scheme can resist internal keyword guessing attacks under the random oracle model.Simulation results show that the proposed scheme has higher computational efficiency compared with similar schemes.

Routing algorithm for railway monitoring linear WSN based on improved PSO

Cuiran LI, Xuejie WANG, Jianli XIE, Anqi LYU

2022, 43(5):  155-165.  doi:10.11959/j.issn.1000-436x.2022109

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To solve the problems of short network lifetime and large data transmission delay, caused by unbalanced node energy consumption of linear wireless sensor network in railway monitoring scenario, a routing algorithm based on particle swarm optimization theory and breadth first search was proposed.The fitness function was constructed based on the relative energy consumption, spacing and load of candidate cluster heads.The local search ability of particle swarm algorithm was enhanced by adjusting the inertia weight coefficient to set up the cluster head optimal set.Meanwhile, a path cost function driven by energy consumption and delay was built up, and the optimal main path from the source node to the sink node was obtained by breadth first search.Lastly, a Q-learning alternative path updating and route maintenance mechanism based on discrete Markov decision process (MDP) was designed.Simulation results show that the proposed algorithm can balance the node energy consumption effectively, and has also advantages in prolonging the network lifetime and reducing the data transmission delay.

CSI feedback algorithm based on RM-Net for massive MIMO systems in high-speed mobile environment

Yong LIAO, Shiyi WANG

2022, 43(5):  166-176.  doi:10.11959/j.issn.1000-436x.2022097

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Aiming at the complex and changeable channel characteristics in high-speed mobile environment, and the influence of additive noise and nonlinear effects, a residual mixing network (RM-Net) for massive MIMO CSI feedback was proposed.By learning the spatial structure and temporal correlation of high-speed mobile channel, the network was able to remove massive MIMO channel noise, and the CSI compression rate and recovery quality could be significantly improved.System simulation results show that RM-Net can eliminate the influence of additive noise in high-speed mobile scenarios, learn and adapt to the channel characteristics of sparse and double-selective fading channels, and still has good performance under the conditions of high compression rate and low signal-to-noise ratio.The proposed algorithm performance is much better than other CS-based and DL-based CSI feedback algorithms.

Comprehensive Reviews

LEO mega-constellation network:networking technologies and state of the art

Quan CHEN, Lei YANG, Jianming GUO, Xingchen LI, Yong ZHAO, Xiaoqian CHEN

2022, 43(5):  177-189.  doi:10.11959/j.issn.1000-436x.2022075

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The emerging low earth orbit (LEO) mega-constellation network (MCN) represented by Starlink and OneWeb were studied.The system architecture and basic working modes were introduced, and the main features of the emerging broadband MCN were summarized.Based on the system architecture of MCN, the methodology and research progress of five key technologies were investigated and summarized, including network topology dynamics management, space-ground handover scheme, high-efficiency routing algorithm design, gateway placement design, network simulation and performance evaluation.The focus was on recent mega-constellation-related studies.The challenges caused by the large scale and complexity of MCN and the applicability of existing techniques and solutions in MCN were analyzed.

Research progress of deep learning-based object detection of optical remote sensing image

Yurong LIAO, Haining WANG, Cunbao LIN, Yang LI, Yuqiang FANG, Shuyan NI

2022, 43(5):  190-203.  doi:10.11959/j.issn.1000-436x.2022071

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Object detection is the core issue in the interpretation of optical remote sensing images, and it is widely used in fields such as intelligence reconnaissance, target monitoring, and disaster rescue.Firstly, combined with the research progress of deep learning optical remote sensing image object detection algorithms, the two types of algorithms based on candidate regions and regression analysis were reviewed.Secondly, the improvement of object detection algorithms for four types of common task-specific scenes were summarized, including rotating objects, small objects, multi-scales, and dense objects.Then, combined with commonly used remote sensing image data sets, the performance of different algorithms was compared and analyzed.Finally, the issues worthy of attention in remote sensing image object detection in the future were prospected, and ideas for follow-up related research were provided.

Correspondences

Strong measurement method of evidence conflict based on earth mover’s distance

Xin WANG, Wei FU

2022, 43(5):  204-213.  doi:10.11959/j.issn.1000-436x.2022094

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Aiming at the problem that the conflict factor k in D-S evidence theory cannot effectively measure the degree of conflict between two bodies of evidence (BoEs), the expected features of evidence conflict strong measurement function (ECSMF) were proposed, and then a new method of evidence conflict measurement based on earth mover’s distance (EMD)was put forward.The same number of focal elements between different BoEs was not required and the evidence conflict with non-singleton propositions could be directly calculate.The proposed method did not require The theory and experiments show that the size of conflict measure proposed can correctly represent the degree of conflict between two BoEs, and has all the expected features of ECSMF, which is an effective method of evidence conflict strong measurement.

Research on HMM based link prediction method in heterogeneous network

Rong QIAN, Jianting XU, Kejun ZHANG, Hongyu DONG, Fangyuan XING

2022, 43(5):  214-225.  doi:10.11959/j.issn.1000-436x.2022095

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In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering could effectively capture the structural information of heterogeneous network, the k-means algorithm was improved to obtain the initial clustering center method based on the minimum distance mean square error, and it was applied to the hidden Markov model, first-order cluster hidden markov model (C-HMM⁽¹⁾) link prediction method, and a link prediction method for heterogeneous network with second-order cluster hidden Markov model (C-HMM⁽²⁾) were designed.Further, considering the feature information of the data, a link prediction method called ME-HMM that combined the maximum entropy model and the second-order Markov model was proposed.The experimental results show that the ME-HMM has higher link prediction accuracy than the C-HMM, and the ME-HMM method has better performance than the C-HMM method because it fully considers the feature information of the data.