Shuren Zhou^1,2,*, Wenlong Liang^1,2, Junguo Li^1,2, Jeong-Uk Kim³

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 11-24, 2018, DOI:10.32604/cmc.2018.02617

Abstract Road traffic sign recognition is an important task in intelligent transportation system. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, it presents a road traffic sign recognition algorithm based on a convolutional neural network. In natural scenes, traffic signs are disturbed by factors such as illumination, occlusion, missing and deformation, and the accuracy of recognition decreases, this paper proposes a model called Improved VGG (IVGG) inspired by VGG model. The IVGG model includes 9 layers, compared with the original VGG model, it is added max-pooling… More >

Huiyu Sun^1,*, Suzanne McIntosh¹

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 1-9, 2018, DOI:10.32604/cmc.2018.03684

Abstract The majority of big data analytics applied to transportation datasets suffer from being too domain-specific, that is, they draw conclusions for a dataset based on analytics on the same dataset. This makes models trained from one domain (e.g. taxi data) applies badly to a different domain (e.g. Uber data). To achieve accurate analyses on a new domain, substantial amounts of data must be available, which limits practical applications. To remedy this, we propose to use semi-supervised and active learning of big data to accomplish the domain adaptation task: Selectively choosing a small amount of datapoints from a new domain while… More >

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 requires the embedded image looks… More >

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 learning. Among them, MTS performs… More >

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 this work, a highly efficient… More >

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 target nodes work for one… More >

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 reversible data hiding scheme in… More >

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 retrieval efficiency of the encrypted… More >

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 designed to filter out the… More >

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. Second, due to each type… More >