Current Issue

25 December 2019, Volume 40 Issue 12

Previous Issue    Next Issue

Papers

Efficient pairing-free CP-ABE based on ordered binary decision diagram

Sheng DING,Jin CAO,Hui LI

2019, 40(12):  1-8.  doi:10.11959/j.issn.1000-436x.2019234

Asbtract ( 369 )   HTML ( 26)   PDF (778KB) ( 756 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

To improve the computational efficiency of ABE,its access structure was optimized and a pairing-free CP-ABE scheme based on ordered binary decision diagram (OBDD) was proposed.Based on the elliptic curve cryptography,the complex bilinear pairing operation in traditional CP-ABE was replaced with the relatively lightweight scalar multiplication,thus the overall computation overhead was reduced.And OBDD was used as the access structure of CP-ABE,which can not only represent any Boolean expression about attributes,but also support both positive and negative attributes.The length of the key was independent of the number of attributes and the length of the ciphertext was only related to the number of valid paths in the access policy.The security and performance analysis show that the scheme can resist chosen plaintext attack under the decisional Diffie-Hellman (DDH) assumption,and the computation efficiency can meet the practical application requirements of Internet of things.

Privacy risk adaptive access control model via evolutionary game

Hongfa DING,Changgen PENG,Youliang TIAN,Shuwen XIANG

2019, 40(12):  9-20.  doi:10.11959/j.issn.1000-436x.2019240

Asbtract ( 389 )   HTML ( 26)   PDF (889KB) ( 475 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Aiming at the problem that in the private sensitive date centralized and opening information systems,a fine-grained and self-adaptive access control model for privacy preserving is desperately needed,thus the balance between privacy preserving and data access utility should be achieved,a rational multi-player risk-adaptive based access control model for privacy preserving was proposed.Firstly,the privacy risk values of access request and requester were formulized by the private information quantity of the requested dataset,and by using Shannon information.Secondly,a risk-adaptive based access control evolutionary game model was constructed by using evolutionary game under the supposing of bounded rational players.Furthermore,dynamic strategies of participants were analyzed by using replicator dynamics equation,and the method of choosing evolutionary stable strategy was proposed.Simulation and comparison results show that,the proposed model is effective to dynamically and adaptively preserve privacy and more risk adaptive,and dynamic evolutionary access strategies of the bounded rational participants are more suitable for practical scenarios.

k-error linear complexity of q-ary sequence of period p²

Chenhuang WU,Chunxiang XU,Xiaoni DU

2019, 40(12):  21-28.  doi:10.11959/j.issn.1000-436x.2019230

Asbtract ( 185 )   HTML ( 9)   PDF (839KB) ( 713 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Based on element statistics in a matrix,a new efficient computing method for computing the k-error linear complexity of q-ary sequence of period p²was proposed,where p,q were odd primes and q modulo p²was primitive.A general result and a concrete proof were showed.To verify the correctness of the result,two kinds of q-ary sequence of period p²were illustrated.Because the new method does not need iterative calculation and when it is implemented by program and compared with existing algorithms,the results show that the proposed new algorithm is significantly more efficient in calculating k-error linear complexity of q-ary sequence of period p².

High-performance and high-concurrency encryption scheme for Hadoop platform

Wei JIN,Mingjie YU,Fenghua LI,Zhengkun YANG,Kui GENG

2019, 40(12):  29-40.  doi:10.11959/j.issn.1000-436x.2019224

Asbtract ( 365 )   HTML ( 29)   PDF (1315KB) ( 1010 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

To address the problem that as preventing data leakage on Hadoop platform,the existing encryption schemes suffer from several problems (e.g.,single encryption algorithm,complicated key management,low encryption performance) and they cannot protect data stored in Hadoop effectively,a high-performance encryption and key management scheme for Hadoop was proposed.Firstly,a three-level key management system was extended with the domestic commercial cipher algorithm.Then,a new data structure for encryption zone key to reduce time consumption was designed.Finally,the computing process of data stream in parallel was scheduled.The experimental results show that compared with the existing Hadoop schemes,the proposed scheme can improve the efficiency of key management,and can speed up file encryption.

Self-correcting complex semantic analysis method based on pre-training mechanism

Qing LI,Jiang ZHONG,Lili LI,Qi LI

2019, 40(12):  41-50.  doi:10.11959/j.issn.1000-436x.2019195

Asbtract ( 297 )   HTML ( 14)   PDF (1180KB) ( 417 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

In the process of knowledge service,in order to meet the fragmentation management needs of intellectualization,knowledge ability,refinement and reorganization content resources.Through deep analysis and mining of semantic hidden knowledge,technology,experience,and information,it broke through the existing bottleneck of traditional semantic parsing technology from Text-to-SQL.The PT-Sem2SQL based on the pre-training mechanism was proposed.The MT-DNN pre-training model mechanism combining Kullback-Leibler technology was designed to enhance the depth of context semantic understanding.A proprietary enhancement module was designed that captured the location of contextual semantic information within the sentence.Optimize the execution process of the generated model by the self-correcting method to solve the error output during decoding.The experimental results show that PT-Sem2SQL can effectively improve the parsing performance of complex semantics,and its accuracy is better than related work.

Evaluation and protection of multi-level location privacy based on an information theoretic approach

Wenjing ZHANG,Qiao LIU,Hui ZHU

2019, 40(12):  51-59.  doi:10.11959/j.issn.1000-436x.2019235

Asbtract ( 491 )   HTML ( 40)   PDF (824KB) ( 885 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

A privacy metric based on mutual information was proposed to measure the privacy leakage occurred when location data owner trust data users at different levels and need to publish the distorted location data to each user according to her trust level,based on which an location privacy protection mechanism (LPPM)was generated to protect user’s location privacy.In addition,based on mutual information,a metric was proposed to measure the privacy leakage caused by attackers obtaining different levels of distorted location data and then performing inference attack on the original location data more accurately.Another privacy metric was also proposed to quantify the information leakage occurred in the scenario based on mutual information.In particular,the proposed privacy mechanism was designed by modifying Blahut-Arimoto algorithm in rate-distortion theory.Experimental results show the superiority of the proposed LPPM over an existing LPPM in terms of location privacyutility tradeoff in both scenarios,which is more conspicuous when there are highly popular locations.

Software-defined networking QoS optimization based on deep reinforcement learning

Julong LAN,Xueshuai ZHANG,Yuxiang HU,Penghao SUN

2019, 40(12):  60-67.  doi:10.11959/j.issn.1000-436x.2019227

Asbtract ( 1071 )   HTML ( 118)   PDF (1269KB) ( 1323 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

To solve the problem that the QoS optimization schemes which based on heuristic algorithm degraded often due to the mismatch between parameters and network characteristics in software-defined networking scenarios,a software-defined networking QoS optimization algorithm based on deep reinforcement learning was proposed.Firstly,the network resources and state information were integrated into the network model,and then the flow perception capability was improved by the long short-term memory,and finally the dynamic flow scheduling strategy,which satisfied the specific QoS objectives,were generated in combination with deep reinforcement learning.The experimental results show that,compared with the existing algorithms,the proposed algorithm not only ensures the end-to-end delay and packet loss rate,but also improves the network load balancing by 22.7% and increases the throughput by 8.2%.

Energy-efficient strategy for data migration and merging in Storm

Yonglin PU,Jiong YU,Liang LU,Ziyang LI,Chen BIAN,Bin LIAO

2019, 40(12):  68-85.  doi:10.11959/j.issn.1000-436x.2019226

Asbtract ( 246 )   HTML ( 9)   PDF (1822KB) ( 437 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Storm is suffering the problems of high energy consumption but low efficiency.Aiming at this problem,the resource constraint model,the optimal principle of data reorganization in executors and node voltage reduction principle were proposed based on the analysis of the architecture and topology of Storm,and further the energy-efficient strategy for data migration and merging was put forward in Storm(DMM-Storm),which was composed of resource constraint algorithm,data migration and merging algorithm as well as node voltage reduction algorithm.The resource constraint algorithm estimates whether work nodes are appropriate for data migration according to the resource constraint model.The data migration and merging algorithm designs an optimal method to migrate data according to the the optimal principle of data reorganization in executors.The node voltage reduction algorithm reduces voltage of work nodes according to node voltage reduction principle.The experimental results show that the DMM-Storm can reduce energy consumption efficiently without affecting the performance of cluster compared with the existing researches.

Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity

Xuanli WU,Xu CHEN

2019, 40(12):  86-97.  doi:10.11959/j.issn.1000-436x.2019205

Asbtract ( 225 )   HTML ( 18)   PDF (969KB) ( 290 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.

Channel estimation method based on compressive sensing for FBMC/OQAM system

Weina YUAN,Qiu YAN

2019, 40(12):  98-104.  doi:10.11959/j.issn.1000-436x.2019239

Asbtract ( 237 )   HTML ( 32)   PDF (953KB) ( 618 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

In mobile-to-mobile sensor networks,the channel estimation for FBMC/OQAM system can be investigated as a compressive sensing problem to raise frequency spectrum efficiency by exploiting the sparse nature of wireless channels.Firstly,a novel orthogonal matching pursuit algorithm with selection weak strategy and regularization based on Tanimoto coefficient (T-SWROMP) was proposed to improve the accuracy of LS channel estimation.Then,T-SWROMP methods with auxiliary pilot and coding were used to estimate channel frequency response for FBMC/OQAM system.The experimental results demonstrate the proposed method has lower complexity than the traditional SWOMP method.In addition,it achieve best performance among the traditional OMP,SWOMP and ROMP methods under dual-selective channels.

Study on the constructions of optimal almost quaternary sequences with period 2q

Xiuping PENG,Huipu JI,Deliang ZHENG,Xiaoxia NIU

2019, 40(12):  105-113.  doi:10.11959/j.issn.1000-436x.2019225

Asbtract ( 180 )   HTML ( 8)   PDF (1158KB) ( 320 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Based on the Chinese remainder theorem and cyclotomic classes of order 4,the constructions of almost quaternary sequences with period N=2q (where q is an odd prime) was studied.According to the number of “0” in the two positions y(0) and y(q),three types of optimal almost quaternary sequences with optimal balance property and out-of-phase autocorrelation values as{0,-2},{0,2,-2} and {0,-2,-2i,2i} were constructed respectively.Through these constructions,all the almost quaternary sequences constructed are balanced and optimal.These constructed sequences extend the existence range of the balanced optimal quaternary sequences and provide more optimal sequences for practical applications.

Clustering routing protocol based on improved PSO algorithm in WSN

Xiaonian WU,Chuyun ZHANG,Runlian ZHANG,Yaping SUN

2019, 40(12):  114-123.  doi:10.11959/j.issn.1000-436x.2019241

Asbtract ( 363 )   HTML ( 37)   PDF (920KB) ( 1072 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Aiming at the problem that the location distribution of cluster head nodes filtered by wireless sensor network clustering routing protocol was unbalanced and the data transmission path of forwarding nodes was unreasonable,which would increase the energy consumption of nodes and shorten the network life cycle,a clustering routing protocol based on improved particle swarm optimization algorithm was proposed.In the process of cluster head election,a new fitness function was established by defining the energy factor and position equalization factor of the node,the better candidate cluster head node was evaluated and selected,the position update speed of the candidate cluster head nodes was adjusted by the optimized update learning factor,the local search and speeded up the convergence of the global search was expanded.According to the distance between the forwarding node and the base station,the single-hop or multi-hop transmission mode was adopted,and a multi-hop method was designed based on the minimum spanning tree to select an optimal multi-hop path for the data transmission of the forwarding node.Simulation results show that the clustering routing protocol based on improved particle swarm optimization algorithm can elect cluster head nodes and forwarding nodes with more balanced energy and location,which shortened the communication distance of the network.The energy consumption of nodes is lower and more balanced,effectively extending the network life cycle.

Comprehensive Review

Survey of research on application of heuristic algorithm in machine learning

Yanping SHEN,Kangfeng ZHENG,Chunhua WU,Yixian YANG

2019, 40(12):  124-137.  doi:10.11959/j.issn.1000-436x.2019242

Asbtract ( 525 )   HTML ( 48)   PDF (821KB) ( 1902 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.Then,the advantages of the heuristic algorithm were illustrated from its applications in machine learning,including the parameter and structure optimization of neural network and other machine learning algorithms,feature optimization,ensemble pruning,prototype optimization,weighted voting ensemble and kernel function learning.Finally,the heuristic algorithms and their development directions in the field of machine learning were given according to the actual needs.

Correspondences

Policy translation and configuration using dynamic template

Yunchuan GUO,Ling LI,Yongjun LI,Lin CHENG,Jun DU,Lingcui ZHANG

2019, 40(12):  138-148.  doi:10.11959/j.issn.1000-436x.2019236

Asbtract ( 238 )   HTML ( 6)   PDF (1502KB) ( 445 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

To solve the problem of complex,cumbersome and error-prone configuration of security devices caused by the heterogeneous configuration modes in complex networks,a dynamic template-based scheme for translating and configuring policy was proposed.In detail,considering the code’s features,the code-based template for translating policies was constructed to configure the command line conversion,and the keyword comparison method was used to ensure the accuracy of policy configuration.Experiments show that the scalability and the accuracy of the proposed scheme.

Verifiable three-party secure key exchange protocol based on eigenvalue

Yanshuo ZHANG,Zehao WANG,Zhiqiang WANG,Huiyan CHEN

2019, 40(12):  149-154.  doi:10.11959/j.issn.1000-436x.2019233

Asbtract ( 239 )   HTML ( 29)   PDF (922KB) ( 438 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

In order to solve the problem that the traditional key exchange protocol,which was not flexible enough and flawed in security,cannot provide the function of three-party key negotiation,firstly,a simple and flexible three-party key exchange scheme that can resist man-in-the-middle attacks was proposed with the help of secret matrix eigenvalues.However,the validity of key exchange cannot be verified by the scheme,and counterfeiting by middlemen can’t be prevented.Then based on it,the secret matrix was reconstructed,where the matrix order was a large even number,and all the eigenvalues appeared in pairs,similar to the diagonal matrix.Based on the special secret matrix,the verification part which can be used to verify the legitimacy of the communication party was introduced to the scheme,and the verifiable three-party key exchange protocol based on the eigenvalue was given.The protocol not only solved the problem of three-party key exchange,but also verified identity legitimacy.It is proved that it’s feasible to design a three-party key exchange protocol by the eigenvalue.The final protocol is both secure and efficient.

Joint recommendation algorithm based on tensor completion and user preference

Zhi XIONG,Kai XU,Lingru CAI,Weihong CAI

2019, 40(12):  155-166.  doi:10.11959/j.issn.1000-436x.2019231

Asbtract ( 312 )   HTML ( 14)   PDF (1023KB) ( 1247 )   Knowledge map   

Figures and Tables | References | Related Articles | Metrics

Aiming at the problem that existing recommendation algorithms have little regard for user preference,and the recommendation result is not satisfactory,a joint recommendation algorithm based on tensor completion and user preference was proposed.First,a user-item-category 3-dimensional tensor was built based on user-item scoring matrix and item-category matrix.Then,the Frank-Wolfe algorithm was used for iterative calculation to fill in the missing data of the tensor.At the same time,a user category preference matrix and a scoring preference matrix were built based on the 3-dimensional tensor.Finally,a joint recommendation algorithm was designed based on the completed tensor and the two preference matrices,and the differential evolution algorithm was used for parameter tuning.The experimental results show that compared with some typical and newly proposed recommendation algorithms,the proposed algorithm is superior to the compare algorithms,the precision is improved by 1.96% ~ 3.44% on average,and the recall rate is improved by 1.35%~2.40% on average.