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15 July 2018, Volume 4 Issue 7

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Comprehensive Reviews

Research progress on moving target defense for SDN

Jinglei TAN, Hongqi ZHANG, Cheng LEI, Xiaohu LIU, Shuo WANG

2018, 4(7):  1-12.  doi:10.11959/j.issn.2096-109x.2018061

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Software-defined network is based on flexible and open standards,which manages network functions and services by the control layer.And it has the unique advantages of control-separation and centralized control.The moving target defense technology is dedicated to build an ever-changing environment to increase the uncertainty of the network system,which requires a flexible and customizable,centralized and controllable network architecture to implement it.Therefore,the combination of moving target defense and software-defined network have become a more valuable research hotspot.Firstly,the basic concepts of software-defined network and moving target defense were introduced,the security threats of software-defined network was summarized,and the realization model of moving target defense for SDN network was described.Secondly,the technical methods for moving target defense were summarized respectively form the data layer,control layer and application layer of the SDN.Finally,summing up the challenges of existing SDN dynamic defense,and looking forward to the development direction of moving target defense technologies for the SDN.

Overview of searchable encryption research

Ying LI, Chunguang MA

2018, 4(7):  13-21.  doi:10.11959/j.issn.2096-109x.2018062

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With the development of cloud computing,there is an increasing number of companies and individuals outsourcing their data to cloud server in the encrypted form to protect data security and user privacy.As a result,efficient retrieval of encrypted data stored on cloud server has become the issue that users may pay attention to.Searchable encryption (SE) is a cryptographic primitive that supports keyword search over encrypted data,and migrates the cumbersome search operation to the cloud server to utilize its vast computational resources.Reviews previous research according to the different cryptosystems used,and divides SE into two groups,that is symmetric searchable encryption and asymmetric searchable encryption.Based on this classification,first introduces a typical program,and then introduces from the two aspects of the expression of searchable encryption and security.Finally,the need-to-be-solved problems and main research directions are discussed.

Papers

Blockchain-based digital copyright trading system

Li LI,Siqin ZHOU,Qin LIU,Debiao HE

2018, 4(7):  22-29.  doi:10.11959/j.issn.2096-109x.2018060

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In the current era of digitalization and networking,the demand for digital copyright transactions is increasing.The traditional centralized copyright protection system has series of problems such as high registration costs,long work acceptance times,and being vulnerable to tampering by saboteurs.Blockchain as a decentralized network structure and based on P2P network and cryptographic technology,which can establish trust relationship on the network by pure mathematics.Without relying on the middle platform,blockchain technology can naturally alleviate the above problems.With the help of self-regulatory,traceable and decentralized features of blockchain technology and digital copyright trading scenarios,a digital copyright trading system model was designed.The new system is based on the advanced permissioned blockchain provided by IBM.The implementation of copyright registration and copyright transaction can ensure the integrity and tamper-resistant of the information.Finally,the installation time of chain code deployment was tested.The results show that the system is simple to install and has low maintenance costs.Compared with the traditional trusted third party copyright authentication mechanism,the blockchain-based digital rights trading system has a short registration time,no registration fee,and better architecture security and scalability.

Neural network-based link prediction algorithm

Yonghao PAN,Hongtao YU,Shuxin LIU

2018, 4(7):  30-38.  doi:10.11959/j.issn.2096-109x.2018049

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To improve the difference existed in the link prediction accuracy and adaptability of different topology structure similarity based methods,a neural network-based link prediction algorithm,which fused similarity indices by neural network was proposed.The algorithm uses neural network to study the numerical characteristics of different similarity indices,and uses particle swarm optimization to optimize the neural network,and calculates the fusion index by the optimized neural network model.The experiment on the real network data set shows that the prediction accuracy of the algorithm is obviously higher than that before the fusion,and the accuracy is better than the existing methods.

Blockchain-based taffic condition early-warning scheme for VANET

Chunyan LI,Jia ZHAO,Jiqiang LIU,Qiang ZHANG,Lei HAN

2018, 4(7):  39-47.  doi:10.11959/j.issn.2096-109x.2018058

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Road conditions early-warning scheme is effective solution to solve vehicle congestion and traffic accidents of VANET.The current traffic conditions in China as well as the development and application of VANET were analyzed.Combined with blockchain technology,a blockchain-based traffic conditions early-warning scheme for VANET was proposed.The Hyperledger Fabric alliance chain technology platform is used to simulate this scheme.The experimental results show that the scheme is reasonable and feasible.

Combinatorial intrusion detection model based on deep recurrent neural network and improved SMOTE algorithm

Binghao YAN,Guodong HAN

2018, 4(7):  48-59.  doi:10.11959/j.issn.2096-109x.2018056

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Existing intrusion detection models generally only analyze the static characteristics of network intrusion actions,resulting in low detection rate and high false positive rate,and cannot effectively detect low-frequency attacks.Therefore,a novel combinatorial intrusion detection model (DRRS) based on deep recurrent neural network (DRNN) and region adaptive synthetic minority oversampling technique algorithm (RA-SMOTE) was proposed.Firstly,RA-SMOTE divided the low frequency attack samples into different regions adaptively and improved the number of low-frequency attack samples with different methods from the data level.Secondly,the multi-stage classification features were learned by using the level feedback units in DRNN,at the same time,the multi-layer network structure achieved the optimal non-linear fitting of the original data distribution.Finally,the intrusion detection was completed by trained DRRS.The empirical results show that compared with the traditional intrusion detection models,DRRS significantly improves the detection rate of low-frequency attacks and overall detection efficiency.Besides,DRRS has a certain detection rate for unknown new attacks.So DRRS model is effective and suitable for the actual network environment.

Dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm

Qiang CHEN,Caixia LIU,Lingshu LI

2018, 4(7):  60-68.  doi:10.11959/j.issn.2096-109x.2018057

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Dealing with the problem of network resource utilization and the user experience,the network slicing as a novel technology is adopted in 5G.A dynamic resource scheduling strategy for 5G network slicing based on improved greedy algorithm was proposed.In the process of slice scheduling and user scheduling,a two layer slice-user model combined with the improved greedy algorithm was proposed,which ensured the slices with maximum service weight and the highest priority users combined together to complete corresponding services.The global resource optimal problem was transformed into a smaller sub problem by means of the optimal combination of each slice and every user,which improved the network resource utilization and the user experience in the meantime.The Matlab simulation results show that compared with existing algorithms,the proposed method could effective improve the system remaining resource utilization,system average QoE level and system throughput.

Image visualization encryption algorithm based on Shamir threshold secret key sharing

Yifu TAN,Zichen LI

2018, 4(7):  69-76.  doi:10.11959/j.issn.2096-109x.2018063

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An image visualization encryption algorithm with authentication function by using Shamir scheme was proposed.The main idea of this algorithm is to obtain the data by segmenting the binary secret image into blocks.Then,Shamir scheme was used to obtain the sub-secret data and simultaneously sign the secret image with the SM2 signature algorithm.And it would embed the shared data and signature information into carrier images.When the restoration is required,a specified number of sub-secret images are required for information extraction,restoration and authentication.The simulation experiment of the scheme shows that the secret image sharing scheme improves the security of secret image storage and transmission.