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    15 May 2018, Volume 4 Issue 5
    Papers
    Dynamic and heterogeneous Byzantine system in cloud
    Yang CHEN,Hongchao HU,Wenyan LIU,Shumin HUO,Hao LIANG
    2018, 4(5):  1-9.  doi:10.11959/j.issn.2096-109x.2018036
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    In order to improve the intrusion tolerance performance of cloud platforms,the Byzantine system model has been widely used.But the current Byzantine system is difficult to prevent a latent attack effectively,which can destroy the Byzantine system by accumulating the number of executive modules which the attacker controls and making it exceed the tolerance upper limit.To solve the problem,a dynamic and heterogeneous Byzantine system was proposed.In which the executive modules were maximized diversified in configurations such as different operating systems and so on.Meanwhile,every executive module was assigned a lifetime based on the attacker’s ability and the vulnerabilities of the module.The novel system can significantly enhance the intrusion tolerance of the cloud service by diverse and dynamic attack surface,which is verified by simulations.

    Adaptive selection method of differential privacy GAN gradient clipping thresholds
    Peng GUO, Shangping ZHONG, Kaizhi CHEN, Hang CHENG
    2018, 4(5):  10-20.  doi:10.11959/j.issn.2096-109x.2018041
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    A method of adaptive selection of differential privacy GAN gradient clipping threshold was proposed.The method assumes that a small portion of public data that is identically distributed with the private data can be accessed,a batch of data is randomly selected from the public data,a clipping threshold is set as an average gradient norm of the batch of data,and the above operations are iterated until the network converges.The method was verified on the Mnist and Cifar10 data sets.The results show that under a reasonable privacy budget,the accuracy of CNN classifiers is improved by 1%~4% compared with the differential privacy auxiliary classifier GAN,inception scores increased by 0.6~1.2.

    Research on synthesis data generation method for logo recognition
    Yuchao JIANG,Lixin JI,Chao GAO,Shaomei LI
    2018, 4(5):  21-31.  doi:10.11959/j.issn.2096-109x.2018043
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    Aiming at the problem of training sample sparse in Logo recognition task under the deep learning framework,a Logo data synthesis algorithm based on contexts was proposed.The algorithm comprehensively utilizes various types of context information to guide the synthesis of Logo images,such as the interior of Logo object,the neighborhood of Logo object,the link between Logo object and other objects and the scene where Logo object lives in.The experimental results on the FlickrLogos-32 dataset show that the proposed algorithm can improve the performance of the Logo identification algorithm (mAP increase by 8.5%) without relying on additional manual annotation,verifying the effectiveness of the synthesis algorithm.

    Certificate-based cross-domain authentication scheme with anonymity
    Yongshan DING,Lixin LI,Zuohui LI
    2018, 4(5):  32-38.  doi:10.11959/j.issn.2096-109x.2018040
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    Considered the cross-domain authentication of mobile devices in the Internet of things,a certificate based anonymous cross-domain authentication scheme was proposed.First,combined with the characteristics of PKI and IBS,a certificate based signature (CBS) algorithm was proposed,and the security of the proposed CBS scheme was proved.The verification result of the signature in the algorithm was constant,which ensured the anonymity of the authentication entities in the cross-domain process.The algorithm does not contain pairing,and avoids complex certificate management in traditional PKI and the key escrow and distribution of IBS.Then a cross-domain authentication scheme for mobile devices was constructed by combining the proposed signature algorithm.The scheme ensures the anonymity of authentication at the same time.Finally,compared with other schemes,the scheme proposed is more secure and has less computation cost and communication cost.Moreover,the scheme is simple and efficient,and could be applied to the cross-domain authentication of mobile devices.

    Spammer detection technology of social network based on graph convolution network
    Qiang QU, Hongtao YU, Ruiyang HUANG
    2018, 4(5):  39-46.  doi:10.11959/j.issn.2096-109x.2018042
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    In social networks,Spammer send advertisements that are useless to recipients without the recipient's permission,seriously threatening the information security of normal users and the credit system of social networking sites.In order to solve problems of extracting the shallow features and high computational complexity for the existing Spammer detection methods of social networks,a Spammer detection technology based on graph convolutional network(GCN) was proposed.Based on the network structure information,the method introduces the network representation learning algorithm to extract the network local structure feature,and combines the GCN algorithm under the re-regularization technology condition to obtain the network global structure feature to achieve the goal of detecting Spammer.Experiments are done on social network data of Tagged.com.The results show that this method has high accuracy and efficiency.

    Enhanced method based on virtual registers rotation
    Yan PAN,Wei LIN
    2018, 4(5):  47-54.  doi:10.11959/j.issn.2096-109x.2018038
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    Sematic attacks based on the data flow analysis bring big challenges to the code obfuscation.Concerning the data flow of virtual machine based (VM-based) code protection,the method transfers the mapping relation between the virtual registers and the op-code of the bytecode during executing,which means the uncertainty and complexity of the data flow during interpretive execution of the bytecode.In addition,three policies are proposed to address the problem that how to choose the length of rotation for each bytecode,which grows complexity of the protection.Finally,a prototype of VRR-VM (virtual machine protection system based on virtual registers rotation) was implemented.Experiment results show that the method is effective and applicable for anti-reversing.

    RAP detection method based on AP fingerprint
    Qing LI,Ayong YE,Zhiqiang YAO,Aimin CHEN
    2018, 4(5):  55-61.  doi:10.11959/j.issn.2096-109x.2018023
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    The access point (AP) is an integral part of the infrastructure mode in wireless network.While the attacks caused by rogue AP (RAP) divulge a lot of users' privates in a large extent,such as the user's location information,surfing behavior on the Internet and social relations.A RAP detection algorithm based on AP fingerprint was proposed.The validity of AP was judged by the unforgeability and stability of the parameters of beacon frames.And the feasibility and effectiveness of the proposed method were further verified by scheme comparisons and experimental analysis.

    QR code security management system based on WPKI and iris recognition
    Yu FU,Lianliang SUN,Xiaoping WU
    2018, 4(5):  62-68.  doi:10.11959/j.issn.2096-109x.2018037
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    Aiming at the deficiency of existing QR code security technology,a security management system based on WPKI and iris recognition was designed and implemented.The system uses digital certificates to sign the hashed information for the user to verify the source of the QR code based on WPKI technology.Through the public security household registration management system,WPKI/CA system,server and mobile client four subsystems to standardize the management of the production and identification of QR code,and the application for the certificate of the user real name certification combined with biometric identification technology,indirectly realizing the binding of digital certificates and user physical identities to form a set of accountability mechanisms.Test results show that the system can meet accuracy and robustness requirements.

    Reversible data hiding scheme based on asymmetric histogram modification
    Zhiheng LYU,Lei LIU,Si CHEN,Zhaoxia YIN
    2018, 4(5):  69-75.  doi:10.11959/j.issn.2096-109x.2018039
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    A reversible data hiding scheme was improved,using two different forecast methods to calculate the prediction error of the original image,two asymmetric prediction error distribution histogram generated,when making secret information embedded respectively on two asymmetric prediction error distribution histogram in the opposite direction of translation ways.Compared with the traditional scheme,the improved scheme can play better to the complementary advantages of embedding strategy,make as many pixels pixel values compensation occur,further protecting the secret image quality.

Copyright Information
Bimonthly, started in 2015
Authorized by:Ministry of Industry and Information Technology of the People's Republic of China
Sponsored by:Posts and Telecommunications Press
Co-sponsored by:Xidian University, Beihang University, Huazhong University of Science and Technology, Zhejiang University
Edited by:Editorial Board of Chinese Journal of Network and Information Security
Editor-in-Chief:FANG Bin-xing
Executive Editor-in-Chief:LI Feng-hua
Director:YI Dong-shan
Address:F8,You Dian Publisher Building,No.11,Chengshousi Road,Fengtai District,Beijing 100078,PR China
Tel:+8610-81055479, 81055456
Fax:+86-81055464
ISSN 2096-109X
CN 10-1366/TP
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