Open Access

ARTICLE

Xuefeng Xi¹, Victor S. Sheng^1,2,*, Binqi Sun², Lei Wang¹, Fuyuan Hu¹
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 185-198, 2018, DOI:10.3970/cmc.2018.03694
Abstract Multi-target regression is concerned with the simultaneous prediction of multiple continuous target variables based on the same set of input variables. It has received relatively small attention from the Machine Learning community. However, multi-target regression exists in many real-world applications. In this paper we conduct extensive experiments to investigate the performance of three representative multi-target regression learning algorithms (i.e. Multi-Target Stacking (MTS), Random Linear Target Combination (RLTC), and Multi-Objective Random Forest (MORF)), comparing the baseline single-target learning. Our experimental results show that all three multi-target regression learning algorithms do improve the performance of the single-target More >

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2193

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Lin Chen^1,2, Chunfang Yang^1,2,*, Fenlin Liu^1,2, Daofu Gong^1,2, Shichang Ding³
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 199-210, 2018, DOI:10.3970/cmc.2018.02574
Abstract When dealing with the large-scale program, many automatic vulnerability mining techniques encounter such problems as path explosion, state explosion, and low efficiency. Decomposition of large-scale programs based on safety-sensitive functions helps solve the above problems. And manual identification of security-sensitive functions is a tedious task, especially for the large-scale program. This study proposes a method to mine security-sensitive functions the arguments of which need to be checked before they are called. Two argument-checking identification algorithms are proposed based on the analysis of two implementations of argument checking. Based on these algorithms, security-sensitive functions are detected More >

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1413

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Wenjie Liu^1,2,*, Zhenyu Chen², Jinsuo Liu³, Zhaofeng Su⁴, Lianhua Chi⁵
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 211-223, 2018, DOI:10.3970/cmc.2018.02288
Abstract The delegating private quantum computation (DQC) protocol with the universal quantum gate set {X,Z,H,P,R,CNOT} was firstly proposed by Broadbent et al. [Broadbent (2015)], and then Tan et al. [Tan and Zhou (2017)] tried to put forward a half-blind DQC protocol (HDQC) with another universal set {H,P,CNOT,T}. However, the decryption circuit of Toffoli gate (i.e. T) is a little redundant, and Tan et al.’s protocol [Tan and Zhou (2017)] exists the information leak. In addition, both of these two protocols just focus on the blindness of data (i.e. the client’s input and output), but do not consider the More >

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1378

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ARTICLE

Taoyun Zhou^1,2, Baowang Lian¹, Siqing Yang^2,*, Yi Zhang¹, Yangyang Liu^1,3
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 225-245, 2018, DOI:10.3970/cmc.2018.02671
Abstract For situations such as indoor and underground parking lots in which satellite signals are obstructed, GNSS cooperative positioning can be used to achieve high-precision positioning with the assistance of cooperative nodes. Here we study the cooperative positioning of two static nodes, node 1 is placed on the roof of the building and the satellite observation is ideal, node 2 is placed on the indoor windowsill where the occlusion situation is more serious, we mainly study how to locate node 2 with the assistance of node 1. Firstly, the two cooperative nodes are located with pseudo-range… More >

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1392

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Zhifeng Wang¹, Diqun Yan^1,*, Rangding Wang¹, Li Xiang¹, Tingting Wu¹
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 247-259, 2018, DOI:10.3970/cmc.2018.02902
Abstract Speech resampling is a typical tempering behavior, which is often integrated into various speech forgeries, such as splicing, electronic disguising, quality faking and so on. By analyzing the principle of resampling, we found that, compared with natural speech, the inconsistency between the bandwidth of the resampled speech and its sampling ratio will be caused because the interpolation process in resampling is imperfect. Based on our observation, a new resampling detection algorithm based on the inconsistency of band energy is proposed. First, according to the sampling ratio of the suspected speech, a band-pass Butterworth filter is More >

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1543

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Yu Yang^1,2,*, Yuwei Chen^1,2, Yuling Chen², Wei Bi^3,4
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 261-272, 2018, DOI:10.3970/cmc.2018.02736
Abstract The state-of-the-art universal steganalysis method, spatial rich model (SRM), and the steganalysis method using image quality metrics (IQM) are both based on image residuals, while they use 34671 and 10 features respectively. This paper proposes a novel steganalysis scheme that combines their advantages in two ways. First, filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods. In addition, a total variant (TV) filter is also used due to its good performance of preserving image edge properties during filtering.… More >

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1299

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Xiaolan Xie^1,2, Tianwei Yuan^1,*, Xiao Zhou³, Xiaochun Cheng⁴
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 273-283, 2018, DOI:10.3970/cmc.2018.03587
Abstract Container virtual technology aims to provide program independence and resource sharing. The container enables flexible cloud service. Compared with traditional virtualization, traditional virtual machines have difficulty in resource and expense requirements. The container technology has the advantages of smaller size, faster migration, lower resource overhead, and higher utilization. Within container-based cloud environment, services can adopt multi-target nodes. This paper reports research results to improve the traditional trust model with consideration of cooperation effects. Cooperation trust means that in a container-based cloud environment, services can be divided into multiple containers for different container nodes. When multiple More >

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1478

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ARTICLE

Yuhong Zhang^1,*, Qinqin Wang¹, Yuling Li¹, Xindong Wu²
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 285-297, 2018, DOI:10.3970/cmc.2018.02604
Abstract Recently, the effectiveness of neural networks, especially convolutional neural networks, has been validated in the field of natural language processing, in which, sentiment classification for online reviews is an important and challenging task. Existing convolutional neural networks extract important features of sentences without local features or the feature sequence. Thus, these models do not perform well, especially for transition sentences. To this end, we propose a Piecewise Pooling Convolutional Neural Network (PPCNN) for sentiment classification. Firstly, with a sentence presented by word vectors, convolution operation is introduced to obtain the convolution feature map vectors. Secondly, More >

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1485

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Yuyu Chen¹, Bangxu Yin², Hongjie He², Shu Yan², Fan Chen^2,*, Hengming Tai³
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 299-312, 2018, DOI:10.3970/cmc.2018.03179
Abstract To improve the security and quality of decrypted images, this work proposes a reversible data hiding in encrypted image based on iterative recovery. The encrypted image is firstly generated by the pixel classification scrambling and bit-wise exclusive-OR (XOR), which improves the security of encrypted images. And then, a pixel-type-mark generation method based on block-compression is designed to reduce the extra burden of key management and transfer. At last, an iterative recovery strategy is proposed to optimize the marked decrypted image, which allows the original image to be obtained only using the encryption key. The proposed More >

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1564

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ARTICLE

Chuanlong Li^1,2,*, Yumeng Jiang³, Marta Cheslyar¹
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 313-324, 2018, DOI:10.3970/cmc.2018.03950
Abstract Deep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which… More >

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1542

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Shuaiwei Zhang¹, Xiaoyuan Yang^1,*, Weidong Zhong¹, Yujuan Sun²
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 325-338, 2018, DOI:10.3970/cmc.2018.03611
Abstract As one of the typical method for side channel attack, DPA has become a serious trouble for the security of encryption algorithm implementation. The potential capability of DPA attack induces researchers making a lot of efforts in this area, which significantly improved the attack efficiency of DPA. However, most of these efforts were made based on the hypothesis that the gathered power consumption data from the target device were stable and low noise. If large deviation happens in part of the power consumption data sample, the efficiency of DPA attack will be reduced rapidly. In… More >

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1563

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Yongli Tang¹, Huanhuan Lian¹, Zemao Zhao², Xixi Yan^1,*
CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 339-352, 2018, DOI:10.3970/cmc.2018.02965
Abstract With the widespread use of cloud computing technology, more and more users and enterprises decide to store their data in a cloud server by outsourcing. However, these huge amounts of data may contain personal privacy, business secrets and other sensitive information of the users and enterprises. Thus, at present, how to protect, retrieve, and legally use the sensitive information while preventing illegal accesses are security challenges of data storage in the cloud environment. A new proxy re-encryption with keyword search scheme is proposed in this paper in order to solve the problem of the low… More >

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