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    25 May 2018, Volume 39 Issue 5
    Papers
    Image encryption method based on multiple-order fractional discrete Tchebichef transform and generating sequence
    Bin XIAO,Wenming SHI,Weisheng LI,Jianfeng MA
    2018, 39(5):  1-10.  doi:10.11959/j.issn.1000-436x.2018072
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    Fractional transform based image encryption methods have been widely studied in recent years.However,most of the existing fractional transform based image encryption methods are defined in the complex field.Thus,the encrypted images contain both phase and amplitude information,which is not conducive to transmission and storage.Moreover,some encryption methods that meet the requirements of reality-preserving have problems of relatively single keys,lacking of sensitivity and so on.An image encryption method was proposed based on multiple-order fractional discrete Tchebichef transform and generating sequence.The proposed method used randomly generated row and column vectors and generating sequence generated by Chaotic sequences as keys to encrypt images,which not only satisfied property of reality-preserving transmission but also greatly expanded the key space.The experimental results further demonstrate that the proposed encryption method can resist a variety of attacks,and decrypted images are almost non-distored,which indicate excellent encryption effect,sufficient security and robustness of the method.

    Detection method of LDoS attacks based on combination of ANN & KPCA
    Zhijun WU,Liang LIU,Meng YUE
    2018, 39(5):  11-22.  doi:10.11959/j.issn.1000-436x.2018073
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    Low-rate denial-of-service (LDoS) attack is a new type of attack mode for TCP protocol.Characteristics of low average rate and strong concealment make it difficult for detection by traditional DoS detecting methods.According to characteristics of LDoS attacks,a new LDoS queue future was proposed from the router queue,the kernel principal component analysis (KPCA) method was combined with neural network,and a new method was present to detect LDoS attacks.The method reduced the dimensionality of queue feature via KPCA algorithm and made the reduced dimension data as the inputs of neural network.For the good sell-learning ability,BP neural network could generate a great LDoS attack classifier and this classifier was used to detect the attack.Experiment results show that the proposed approach has the characteristics of effectiveness and low algorithm complexity,which helps the design of high performance router.

    Security analysis of weighted network anonymity based on singular value decomposition
    Yong ZENG,Lingjie ZHOU,Zhongyuan JIANG,Zhihong LIU,Jianfeng MA
    2018, 39(5):  23-33.  doi:10.11959/j.issn.1000-436x.2018074
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    The security of anonymous method based on singular value decomposition (SVD) in the privacy preserving of weighted social network was analyzed.The reconstruction method in network with integer weights and the inexact reconstruction method in network with arbitrary weighted were proposed.The ε N -tolerance was definited to measure its safety.It was also pointed out that the upper bound of ε (the reconfigurable coefficient) obtained in current spectral theories was so conservative that lacks of guidance.The reconfigurable coefficients of random networks,Barabasi-Albert networks,small world networks and real networks were calculated by experiment.Moreover,the reconfigurable coefficients of double perturbation strategies based on SVD were also tested.Experimental results show that weighted social networks have different tolerances on spectrum loss,and there is a close relationship between its tolerance and network parameters.

    Joint admission control algorithm based on load transfer in heterogeneous networks
    Weiwei XIA,Zhaoming DING,Lianfeng SHEN
    2018, 39(5):  34-47.  doi:10.11959/j.issn.1000-436x.2018075
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    A load-transfer-based joint admission control (LJAC) algorithm in heterogeneous networks was proposed.The access requirements of users were admitted based on load balancing,the dynamic load transfer of traffics in the overlapping coverage areas of heterogeneous networks were introduced,and the influence of such factors as the layout of heterogeneous networks and the vertical handoff was considered in the algorithm.The integrated system of heterogeneous networks was modeled as a multidimensional Markov chain,the steady-state probabilities were obtained and the quality of service (QoS) performance metrics were derived.Based on the Poisson point process theory,the upper bound of capacity of the heterogeneous networks satisfying QoS limitations was obtained.The admission control parameters of the integrated system of heterogeneous networks were optimized in order to maximize the resource utilization rate as well as guaranteeing the QoS of users.The simulation results demonstrate lower traffic blocking probability,lower failure probability of vertical handoff requirements,and larger system capacity gain can be achieved by using the proposed LJAC algorithm.

    Secure and efficient token based roaming authentication scheme for space-earth integration network
    Kaiping XUE,Yongjin MA,Jia’nan HONG,Jie XU,Qingyou YANG
    2018, 39(5):  48-58.  doi:10.11959/j.issn.1000-436x.2018076
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    Aiming at the problem of prolongation and instability of satellite and terrestrial physical communication links in the space-earth integration network,a two-way token based roaming authentication scheme was proposed.The scheme used the characteristics of the computing capability of the satellite nodes in the network to advance the user authentication process from the network control center (NCC) to the access satellite.The satellite directly verified the token issued by the NCC to verify the user's identity.At the same time,the token mechanism based on the one-way accumulator achieved the user's dynamic join,lightweight user self-service customization and billing,and the introduction of Bloom Filter enabled effective user revocation and malicious access management.Compared with the existing scheme,the scheme can guarantee the security of roaming authentication and significantly reduce the calculation and communication overhead of the authentication and key negotiation process.

    Cloud data secure deduplication scheme via role-based symmetric encryption
    Jinbo XIONG,Yuanyuan ZHANG,Youliang TIAN,Zuobin YING,Qi LI,Rong MA
    2018, 39(5):  59-73.  doi:10.11959/j.issn.1000-436x.2018077
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    The rapid development of cloud computing and big data technology brings prople to enter the era of big data,more and more enterprises and individuals outsource their data to the cloud service providers.The explosive growth of data and data replicas as well as the increasing management overhead bring a big challenge to the cloud storage space.Meanwhile,some serious issues such as the privacy disclosure,authorized access,secure deduplication,rekeying and permission revocation should also be taken into account.In order to address these problems,a role-based symmetric encryption algorithm was proposed,which established a mapping relation between roles and role keys.Moreover,a secure deduplication scheme was proposed via role-based symmetric encryption to achieve both the privacy protection and the authorized deduplication under the hierarchical architecture in the cloud computing environment.Furthermore,in the proposed scheme,the group key agreement protocol was utilized to achieve rekeying and permission revocation.Finally,the security analysis shows that the proposed role-based symmetric encryption algorithm is provably secure under the standard model,and the deduplication scheme can meet the security requirements.The performance analysis and experimental results indicate that the proposed scheme is effective and efficient.

    Pseudo 4D projective coordinate-based multi-base scalar multiplication
    Ming XU,Liang SHI
    2018, 39(5):  74-84.  doi:10.11959/j.issn.1000-436x.2018078
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    In order to address the problem of elliptic curve cryptosystem (ECC) for the expensive cost in scalar multiplication and the vulnerability to the power analysis attacks,a pseudo 4D projective coordinate-based multi-base scalar multiplication was proposed to optimize group operation layer and scalar multiplication operation layer,which aimed at increasing the performance of ECC and resisting common power analysis attacks.Experimental results show that compared with the state-of-the-art algorithms,the proposed algorithm decreases 5.71% of point doubling cost,3.17% of point tripling cost,and 8.74% of point quintupling cost under discrete group operations.When the key length is 160 bit,the proposed algorithm decreases 36.32% of point tripling cost,17.42% of point quintupling cost,and 8.70% of the system cost under continuous group operations.The analyzing of power consumption wave shows that the proposed algorithm can resist SPA and DPA attack.

    Dynamic game and reliable recommendation based transferring reputation mechanism for mobile cloud computing
    Hui LIN,Mengyang YU,Youliang TIAN,Yijie HUANG
    2018, 39(5):  85-93.  doi:10.11959/j.issn.1000-436x.2018079
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    The booming development of the mobile internet and cloud computing leads to the emerging of many mobile cloud platforms based services.However,since mobile users store lots of data and privacy information in the cloud when they are using the mobile cloud services,they are facing multiple increasingly serious security threats such as data leaks and privacy exposures.The data security and privacy protection was investigated in mobile cloud computing,aiming at the internal bad mouthing attacks and mobile attacks.A dynamic game and reliable recommendation based transferring reputation mechanism was proposed.First,a dynamic game based recommendation incentive mechanism was proposed.Secondly,a reliable recommendation reputation evaluation model was established based on the incentive mechanism.Last,a novel transferring reputation mechanism was proposed that combined the above mentioned incentive mechanism and reputation evaluation model.Simulation results demonstrate the proposed transferring reputation mechanism can defend against the internal bad mouthing attacks and mobile attacks effectively,enhance the credibility of mobile terminals and improve the data security and privacy protection of mobile cloud services.

    Key storage management scheme based on keyed hash tree with state
    Xiangyu WANG,Jianfeng MA,Yinbin MIAO,Kai ZHANG,Qiying WU
    2018, 39(5):  94-102.  doi:10.11959/j.issn.1000-436x.2018080
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    To solve the problem of massive keys storage caused by multi-source data encryption in ciphertext retrieval system,a key storage scheme based on keyed hash tree with state was proposed.The scheme computes encryption key according to the root key and key derivation tree,and just needs to store the root key and the tree structure,which greatly reduces the key storage costs.In addition,the scheme manages key revocation according to the revocation state value,thereby solving the problem of key revocation and structure update.Strict security analysis shows that the partial data key disclosure does not leak the data confidentiality of remaining data,and the performance analysis using real-world dataset shows that the proposed key storage management scheme is acceptable in ciphertext retrieval system.

    Automatic method for searching integral distinguishers of ARX block ciphers
    Ya HAN,Mingsheng WANG
    2018, 39(5):  103-110.  doi:10.11959/j.issn.1000-436x.2018081
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    Firstly,based on three subsets division property propagation technique,the propagation function of the K-set and L-set of ARX block ciphers was constructed respectively.All vectors in L-set affected the propagation of K-set when propagate through xored round key operation.With SAT/SMT solver,round reduced integral propagation functions of ARX block ciphers could be established.Finally,by exhausting all possible input integral characteristics with proper data complexity,round reduced integral distinguishers of ARX block ciphers could be found.The proposed method can be used for searching integral distinguishers of ARX block ciphers including SIMON-like family block ciphers,HIGHT,SPECK family block ciphers and LEA effectively.

    Multi-label feature selection algorithm based on joint mutual information of max-relevance and min-redundancy
    Li ZHANG,Cong WANG
    2018, 39(5):  111-122.  doi:10.11959/j.issn.1000-436x.2018082
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    Feature selection has played an important role in machine learning and artificial intelligence in the past decades.Many existing feature selection algorithm have chosen some redundant and irrelevant features,which is leading to overestimation of some features.Moreover,more features will significantly slow down the speed of machine learning and lead to classification over-fitting.Therefore,a new nonlinear feature selection algorithm based on forward search was proposed.The algorithm used the theory of mutual information and mutual information to find the optimal subset associated with multi-task labels and reduced the computational complexity.Compared with the experimental results of nine datasets and four different classifiers in UCI,the proposed algorithm is superior to the feature set selected by the original feature set and other feature selection algorithms.

    Secure data sharing scheme supporting efficient synchronous evolution for ciphertext and key
    Xincheng YAN,Yue CHEN,Hongyong JIA,Yanru CHEN,Xinyue ZHANG
    2018, 39(5):  123-133.  doi:10.11959/j.issn.1000-436x.2018083
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    The static property of stored ciphertext in cloud increases the probability that an attacker can crack the ciphertext by obtaining a key,while ciphertext and key updates based on key distribution and re-encryption are excessively expensive.For this problem,a secure data sharing scheme supporting efficient synchronous evolution for ciphertext and key (CKSE-SDS) was proposed.By introducing cryptography accumulator in broadcast encryption,mimicry transformation factor could be constructed supporting time-hopping periodically and efficient synchronous evolution for ciphertext and key could be achieved based on dynamic segmentation and fusion of ciphertext and key,which reduced certainty in the process of encryption and key distribution and increased the difficulty for attackers exploiting security vulnerabilities to obtain key to crack ciphertext as well.Theoretical analysis and security proofs show that the proposed scheme can support secure and efficient data access as well as reduce the probability of a successful attack effectively for an attacker,which can also enhance the system’s active security defense capability.

    Spatio-temporal aware privacy-preserving scheme in LBS
    Weihao LI,Sheng DING,Jiajie MENG,Hui LI
    2018, 39(5):  134-142.  doi:10.11959/j.issn.1000-436x.2018084
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    Location-based service (LBS) brings a lot of conveniences in people’s daily life,but the conveniences are accompanied with the leaking of privacy.A dummy-based location-preserving scheme was proposed,which took the correlation between spatial issues and temporal issues into account.Two algorithms were included in this scheme,map dividing algorithm and dummy contents determining algorithm.The map dividing algorithm divided the map into discrete location cells by Voronoi Diagram to ensure these discrete location cells were not adjacent to each other.The dummy contents determining algorithm replaced the query content in previous moment by the intending location in next moment,which efficiently avoided the adversary inferring mobile users’ sensitive information according to the correlation between spatial issues and temporal issues.The simulation experiments show that the proposed scheme is effective and efficient.

    Research on cloud computing users’ public safety trust model based on scorecard-random forest
    Shengli ZHOU,Canghong JIN,Lifa WU,Zheng HONG
    2018, 39(5):  143-152.  doi:10.11959/j.issn.1000-436x.2018085
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    Traditional cloud computing trust models mainly focused on the calculation of the trust of users’ behavior.In the process of classification and evaluation,there were some problems such as ignorance of content security and lack of trust division verification.Aiming to solve these problems,cloud computing users’ public safety trust model based on scorecard-random forest was proposed.Firstly,the text was processed using Word2Vec in the data preprocessing stage.The convolution neural network (CNN) was used to extract the sentence features for user content tag classification.Then,scorecard method was used to filter the strong correlation index.Meanwhile,in order to establish the users’ public safety trust evaluation model in cloud computing,a random forest method was applied.Experimental results show that the proposed users’ public safety trust evaluation model outperforms the general trust evaluation model.The proposed model can effectively distinguish malicious users from normal users,and it can improve the efficiency of the cloud computing users management.

    Comprehensive Review
    Concepts,issues,and applications of fog computing
    Weijia JIA,Xiaojie ZHOU
    2018, 39(5):  153-165.  doi:10.11959/j.issn.1000-436x.2018086
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    Firstly,the previous work of fog computing was systematically analyzed and summarized.The background of fog computing and the comparison with cloud computing were introduced.Besides,based on the comparison with other computing style,the advantages and characteristics of fog computing were explained.In addition,the architecture of fog computing was described.Moreover,network management and resource scheduling of fog computing were discussed,where the related previous work were summarized and analyzed.At last,the applications of fog computing were described.Taking the intelligent driving and industrial Internet of things applications as examples,the key research issues of fog computing were proposed.

    Correspondences
    Reliability modeling and planning of energy harvesting based on uncertainty theory
    Zhe WANG,Taoshen LI,Jin YE,Zhihui GE,Min WU
    2018, 39(5):  166-176.  doi:10.11959/j.issn.1000-436x.2018087
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    Energy harvesting network is a new form of computer networks.It can convert the environmental energy into usable electric energy,and supply the electrical energy as a primary or secondary power source to the electronic device for network communication.However,the energy harvesting process has great volatility and uncertainty,the traditional analytical method based on probability distribution function to describe the energy collection process can not accurately simulate the actual situation,resulting in higher depletion probability of nodes,then the reliability cannot be guaranteed as a result.For this,the energy harvesting reliability of energy harvesting nodes was defined,represented with the degree of normal operation,respectively set up the node reliability models with no battery and infinite battery.As an example for maximum node achievable rate,the uncertain multilevel programming model based on node reliability was put forward,then the network efficiency was improved under the premise of ensuring node reliability.An energy average allocation (EAA) algorithm was proposed and the upper bound of competitive ratio of the algorithm was proved theoretically.Finally,the actual wind power data was taken as an example to verify the feasibility and effectiveness of the proposed model and method.

    Nondata-aided error vector magnitude performance analysis over κ−μ shadowed fading channel
    Fan YANG,Xiaoping ZENG,Haiwei MAO,Xin JIAN,Derong DU,Xiaoheng TAN,Yiwen GAO
    2018, 39(5):  177-188.  doi:10.11959/j.issn.1000-436x.2018088
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    The performance prediction of wireless system over κ?μ shadowed fading channels was a challenging problem of wireless communications,which affects transmission scheme design seriously.To solve this problem,a novel method of quantifying the κ?μ shadowed fading channels performance based on nondata-aided error vector magnitude (NDA-EVM) was proposed.NDA-EVM was considered as a new metric to evaluate the change of the channels.The unified model to calculate different modulation order of NDA-EVM was analytically derived by maximum likelihood criterion.Moreover,the relationship between the κ?μ distribution and the NDA-EVM was built by using the attenuation factor of the channel as intermediate variable.Thereafter,the lower bounds of the NDA-EVM over the κ?μ shadowed fading channels were formulated,which was also simplified for various typical channels.The theoretical analysis was taken,moreover,numerical results were also conducted to verify the effectiveness of the derived formulation.It shows that NDA-EVM estimation has the lest root mean square error than data-aided signal to noise ratio (DA-SNR) estimation and error vector magnitude (DA-EVM) estimation over the κ?μ shadowed fading channels.The derived lower bounds closely match the theoretical values,especially at low SNR.In addition,the lower bounds are negatively related to all of the parameters of the κ?μ shadowed fading channels,which make it sensitive to the change of the fading channels.

    Algorithm for scenario benefit route planning based on user’s requests
    Nan WANG,Honglei ZHOU,Jinbao LI,Lingli LI
    2018, 39(5):  189-198.  doi:10.11959/j.issn.1000-436x.2018089
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    Most of the existing research for point of interest route planning only consider the static properties of POI,however,the congestion of the hot spots and users’ discontent may greatly reduce the travel quality.In order to increase the tourists’ satisfaction,the dynamic attributes of POI was considered and a route planning algorithm based on user’s requests was proposed.Firstly,Markov-GM(1,1) forecasting algorithm was designed to predict the number of people in each scenic spot.Markov-GM(1,1) could make the average predication error 12.2% lower than the GM(1,1) algorithm by introducing the predication residual.And then,the forward refinement (FR) algorithm was designed which could avoid visiting the unnecessary place and satisfy user’s requests as well.The average solving time of forward refinement algorithm was 9.4% lower than TMT algorithm under the same amount of user’s requests.Finally,based on the factors such as spot popularity,KL divergence of time,visiting order and distance et al,the scenic route profit planning algorithm which could make the number of Rank 1-5 spots 34.8% higher than Time_Based algorithm and 47.3% higher than Rand_GA algorithm.

Copyright Information
Authorized by: China Association for Science and Technology
Sponsored by: China Institute of Communications
Editor-in-Chief: Zhang Ping
Associate Editor-in-Chief:
Zhang Yanchuan, Ma Jianfeng, Yang Zhen, Shen Lianfeng, Tao Xiaofeng, Liu Hualu
Editorial Director: Wu Nada, Zhao Li
Address: F2, Beiyang Chenguang Building, Shunbatiao No.1 Courtyard, Fengtai District, Beijing, China
Post: 100079
Tel: 010-53933889、53878169、
53859522、010-53878236
Email: xuebao@ptpress.com.cn
Email: txxb@bjxintong.com.cn
ISSN 1000-436X
CN 11-2102/TN
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