Table of Content

  

20 March 2017
Volume 52 Issue 3

Research on advertising auction model based on interest

DONG Hong-bin, GOU Nai-kang, YANG Xue

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  1-7.  doi:10.6040/j.issn.1671-9352.4.2016.211

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The keyword auction is very meaningful for search engines and advertisers. We lead the user interest contents into a new mechanism to increase the click through rate. We introduce the interest factor based on GSP and create a new advertising model based on interest. Also, we determine a new ranking rule, payment rule, dominant equilibrium strategy and some other rules. The simulation experiment verify the effectiveness of the advertising auction model.

A new improvable quantum secret sharing scheme

XU Ting-ting, LI Zhi-hui, MA Min

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  8-15.  doi:10.6040/j.issn.1671-9352.2.2016.026

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A new improvable quantum secret sharing scheme which is based on an improvable quantum secret sharing scheme(IQSS scheme)proposed by A.C.A.Nascimento et al. is proposed and it can realize more quantum access structures compared with the IQSS scheme. Furthermore, we prove that all hyperstar quantum access structures can be realized by our scheme in theory. As an application, a total of ten optimal restriction quantum access structures are given for the number of participants at up to 4, and it is proved that 9 of them can be realized by using the new scheme.

Survey on application of data mining via differential privacy

KANG Hai-yan, MA Yue-lei

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  16-23.  doi:10.6040/j.issn.1671-9352.2.2016.053

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The latest results of differential privacy in data mining were surveyed. The basic concepts of differential privacy were introduced. It analyzes the differential privacys research in pattern mining, classification and cluster. It was focused that on the analysis of the principle of some important technology to achieve. And also it was made that comparative analysis of its strengths and weaknesses and algorithm complexity. Finally, the future research of difference privacy under the dynamic data publication and big data environments was discussed.

On the linear complexity of a new generalized cyclotomic sequence with length p³ over GF(l)

LIU Long-fei, YANG Xiao-yuan

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  24-31.  doi:10.6040/j.issn.1671-9352.2.2016.108

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Linear complexity is the most important index for measuring the randomness properties of sequences. Based on the Ding-generalized cyclotomy, a new class of generalized cyclotomic sequences with length p³ over the finite field of power of odd prime order is constructed, and the sequence is balanced. The linear complexity of the sequences is determined using the theory of polynomial over finite field. It is shown that the sequence has good linear complexity, and it can resist attacks from the application of the Berlekamp-Massey algorithm.

The inpainting of affine similarity damaged image based on structure automatic match

YU Wen-jing, BI Dong-xu, YAN Xue-feng

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  32-37.  doi:10.6040/j.issn.1671-9352.0.2016.445

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Based on the character of image structure sparsity, the image structure sparsity operator was defined which can map from original image to structure image. According to the property of the sparse distribution of the similar structure offsets in affine similarity image, this paper indicates the distribution character of similar structure offsets through scientific statistics, with the objective of adaptively winning the superior matching region to the broken region. Experimental results show that the algorithm can achieve the structure match adaptively and can complete the affine broken image effectively.

A study on security enhancement technology for KVM Hypervisor

ZHAO Dan-dan, CHEN Xing-shu, JIN Xin

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  38-43.  doi:10.6040/j.issn.1671-9352.1.2016.083

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To enhance the security capabilities of kernel-based virtual machine(KVM)Hypervisor, a multi-level security capabilities enhancement technology was proposed based on multi vulnerabilities, including Hypervisor type trick, VMX instructions monitoring, the ioctl system call interface protection, dynamical KVM code measurement and anti-unloading technology, to enhance the security capabilities of the KVM Hypervisor and detect some unknown attacks base interfaces of KVM in time. Eventually a prototype system on the full-virtualization platform of KVM was implemented which was called(Security-KVM, Sec-KVM). The experimental result shows that the Sec-KVM is able to hide the virtualization type of the Hypervisor which enhanced the ability of anti-attack of Hypervisor, dynamically measure the integrity of the KVM and the ioctl system call interface which prevented spread of the attacks, and detect some unknown attacks based KVM service interfaces.

Android application protection based on smali code obfuscation

LIU Fang-yuan, MENG Xian-jia, TANG Zhan-yong, FANG Ding-yi, GONG Xiao-qing

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  44-50.  doi:10.6040/j.issn.1671-9352.2.2016.120

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An Android application protection method that is based on code obfuscation of smali code is proposed. The basic idea is that confuses the data flow for the access procedure of register data, and combines opaque predicates technology to confuse the control flow, thus when the attacker reversely analyze the application, the decompiling results will be wrong. The obfuscation method is evaluated from strength, resilience and overhead. The experiment results show that ourcan resist the reverse analysis of current popular reverse tools, such as jeb, dex2jar, dexdump and IDA pro.

Mass diffusion on coupled social networks

DENG Xiao-fang, ZHONG Yuan-sheng, L(¨overU)Lin-yuan, WANG Ming-wen, XIONG Nai-xue

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  51-59.  doi:10.6040/j.issn.1671-9352.0.2016.030

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In the Internet information recommendation application, combining the users social information into recommend systems may further enhance the recommendation accuracy. We transform the social network and the user-commodity bipartite network into a coupled network by considering users as hub nodes and then propose a recommendation algorithm based on the process of mass diffusion dynamics, which integrates the information of friends in the social network and the information of the users selection of items in the user-item bipartite network. It can easily be seen that our approach is an extension of the classical mass diffusion algorithm. Experiments on the real datasets, Friendfeed and Epinions show that the recommendation accuracy of small degree users is improved by 38.48% and 9.17% respectively by comparing our proposed method with the classical mass diffusion algorithm. When the proportion of probe set is 80%, the improvement on recommendation accuracy is 59.05% and 21.62% than that of the classical material diffusion algorithm for all target users. Therefore, the addition of social network information can significantly improve the recommendation accuracy for small degree users.

A software update mechanism for virtual machines in IaaS multi-tenant environment

CHEN Guang-rui, CHEN Xing-shu, WANG Yi-tong, GE Long

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  60-67.  doi:10.6040/j.issn.1671-9352.2.2016.105

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To facilitate the management of software versions in Virtual Machines(VMs)in Infrastructure as a Service(IaaS)environment and reduce the potential security issue is introduced by outdated softwares, a software update mechanism was studied. Firstly, a unified management framework was proposed, and the update tasks are managed by platform instead of users themselves. And then, the mechanism accesses the update service to tenant network using Linux Network Namespace, and isolates the different tenants update services. Lastly, for the same update tasks, this mechanism distributes the software packages in reliable multicast way, which greatly reduces network traffics and saves network resources. The result showed that this mechanism could effectively improve the efficiency of software distribution, save the network resources, reduce the CPU consumption, and ensure the isolation of different tenants update services.

A time-relevant network traffic anomaly detection approach

ZHUANG Zheng-mao, CHEN Xing-shu, SHAO Guo-lin, YE Xiao-ming

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  68-73.  doi:10.6040/j.issn.1671-9352.1.2016.030

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Server behavior characteristics in a time of dynamic correlation characteristics of a clustering method based on the distribution ratio, clustering and density deviation combined to construct a temporal correlation server traffic anomaly detection model. Through the campus network server traffic and long-term observation study found that server traffic characteristics and dynamic correlation time, based on this condition, this article extract the feature server traffic flow at the present time and combines the features of the current moment of time associated with dynamic, using K-means clustering algorithm to detect the outliers of the flow characteristics, and find abnormal server traffic. Experimental results show that the model can effectively detect abnormal server traffic even in the real-world environment. The longer the model applies, the stronger adaptable the algorithm is.

P2P botnet detection method based on fractal and adaptive data fusion

SONG Yuan-zhang, LI Hong-yu, CHEN Yuan, WANG Jun-jie

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  74-81.  doi:10.6040/j.issn.1671-9352.2.2016.001

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A novel P2P botnet detection algorithm based on fractal and adaptive data fusion was proposed. Firstly, it built the single-fractal detection sensor and the multi-fractal detection sensor, and they used the self-similarity under the large time scale and the local singularity under the small time scale to describe the characteristics of network. Kalman filter was used to detect abnormalities of the above characteristics. To get the more accurate detection result, an adaptive data fusion method based on DST(Dempster-Shafer Theory)and DSmT(Dezert-Smarandache Theory)was proposed. Depending on the conflict factor of evidences, DST and DSmT were adaptively utilized to fuse the results of two above detection sensors to get the final result. The side effects on detecting P2P botnet which P2P programs generated are considered. The experiments show that the proposed algorithm is able to detect P2P botnet with high accuracy.

A packet loss concealment scheme based on HMM for mobile audio coding

XIANG Kai, CHEN Shi-hong

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  82-90.  doi:10.6040/j.issn.1671-9352.2.2016.209

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In order to deal with the problem of unexpected large number of continuous packet loss scenarios occur in poor quality of mobile voice transmission and audio communication service, a packet loss concealment scheme based on HMM for ACELP codec is proposed. The scheme utilizes HMM to decide the appropriate packet loss concealment strategy according to the statistical change of larger range of context in audio signal. When a packet loss occurs, the estimation is involved by recovery through status and probability density function. The experiment results show that the objective listening test PESQ score achieves an increase of 0.33 points and subjective listening test CMOS score achieves an increase of 0.05 points when compared with the original scheme employed in AVS-P10 standard.

Cost-sensitive feature selection via manifold learning

HUANG Tian-yi, ZHU William

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  91-96.  doi:10.6040/j.issn.1671-9352.4.2016.080

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In order to get a low-cost subset of original features, we define the cost-distance among the samples and joint it to existing feature selection framework. We combine manifold learning into cost-sensitive feature selection model and develop a corresponding method, namely, cost-sensitive feature selection via manifold learning(CFSM). Most previous cost-sensitive feature selection algorithms rank features individually and select features just using correlation the between the cost and the features. Our cost-sensitive feature selection algorithm selects features not only using the correlation the between the cost and the features but also using the discriminative information implied within data to improve the features selection performance. Experimental results on different real world datasets show the promising performance of CFSM outperforms the state-of-the-arts.

Graded multi-granulation rough set based on weighting granulations and dominance relation

WANG Xiao-yan, SHEN Jia-lan, SHEN Yuan-xia

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  97-104.  doi:10.6040/j.issn.1671-9352.4.2016.159

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It is considered that the quantitative information of the overlap between equivalence classes and a target set in graded multi-granulation rough set. However, the weight of different granularity is ignored. In view of graded multi-granulation rough set and multigranulation rough set based on weighted granulations, it is proposed the model of graded multi-granulation rough set based on weighting granulations and dominance relation. Then, its properties are discussed and a method of granulation reduction is proposed. Finally, the results of examples also show the correctness and effectiveness of the theoretical methods.

Three-way decisions model based on the optimal center covering algorithm

LIU Guo-tao, ZHANG Yan-ping, XU Chen-chu

JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2017, 52(3):  105-110.  doi:10.6040/j.issn.1671-9352.4.2016.216

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The three-way decisions model is the development of the traditional two-way decisions, and its three decisions include positive, negative, and boundary regions. The model widely used in the uncertain or incomplete information areas. The three-way decisions model is based on constructive covering algorithm(CCA)and it could automatic obtain three regions. However, the existing CCA is an uncontrollable random process with the covering center selected, that lead to the three-way decision classification accuracy uncertain. Thus we propose a novel three-way decision model to select the optimal center in constructive covering algorithm(OCCCA). The OCCCA model combines the nearest mean theory, obtains the mean of the one class in the data set, and then chooses the sample that nearest mean as the center. The experimental result shows that our methodology can improve about 5% than traditional CCA in the three-way decisions models classification accuracy.