Muhammad Waqas^{1, 2}, Shanshan Tu^{1, 3, *}, Sadaqat Ur Rehman¹, Zahid Halim², Sajid Anwar², Ghulam Abbas², Ziaul Haq Abbas⁴, Obaid Ur Rehman⁵

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 359-371, 2020, DOI:10.32604/cmc.2020.09821

Abstract Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state… More >

Senbo Chen^{1, 3, *}, Wenan Tan^{1, 2}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 345-358, 2020, DOI:10.32604/cmc.2020.09807

Abstract The problem of influence maximizing in social networks refers to obtaining a set of nodes of a specified size under a specific propagation model so that the aggregation of the node-set in the network has the greatest influence. Up to now, most of the research has tended to focus on monolayer network rather than on multiplex networks. But in the real world, most individuals usually exist in multiplex networks. Multiplex networks are substantially different as compared with those of a monolayer network. In this paper, we integrate the multi-relationship of agents in multiplex networks by considering the existing and relevant… More >

Junxiang Wang^{1, *}, Lin Huang¹, Ying Zhang¹, Yonghong Zhu¹, Jiangqun Ni², Yunqing Shi³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 325-344, 2020, DOI:10.32604/cmc.2020.09784

Abstract To measure the security for hot searched reversible data hiding (RDH) technique, especially for the common-used histogram-shifting based RDH (denoted as HS-RDH), several steganalysis schemes are designed to detect whether some secret data has been hidden in a normal-looking image. However, conventional steganalysis schemes focused on the previous RDH algorithms, i.e., some early spatial/pixel domain-based histogram-shifting (HS) schemes, which might cause great changes in statistical characteristics and thus be easy to be detected. For recent improved methods, such as some adaptive prediction error (PE) based embedding schemes, those conventional schemes might be invalid, since those adaptive embedding mechanism would effectively… More >

Liang Yang^{1, *}, Daojian Zeng², Jianhua Yan³, Yaozhang Sai¹

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 313-323, 2020, DOI:10.32604/cmc.2020.09809

Abstract The Synthetic Aperture Radar (SAR) raw data generator is required to the evaluation of focusing algorithms, moving target analysis, and hardware design. The time-domain SAR simulator can generate the accurate raw data but it needs much time. The frequency-domain simulator not only increases the efficiency but also considers the trajectory deviations of the radar. In addition, the raw signal of the extended scene included static and moving targets can be generated by some frequency-domain simulators. However, the existing simulators concentrate on the raw signal simulation of the static extended scene and moving targets at uniform speed mostly. As for the… More >

Jiangheng Kou¹, Mingxing He^{1, *}, Ling Xiong¹, Zihang Ge², Guangmin Xie¹

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 297-312, 2020, DOI:10.32604/cmc.2020.09758

Abstract With the development of communication technologies, various mobile devices and different types of mobile services became available. The emergence of these services has brought great convenience to our lives. The multi-server architecture authentication protocols for mobile cloud computing were proposed to ensure the security and availability between mobile devices and mobile services. However, most of the protocols did not consider the case of hierarchical authentication. In the existing protocol, when a mobile user once registered at the registration center, he/she can successfully authenticate with all mobile service providers that are registered at the registration center, but real application scenarios are… More >

Yan Liu¹, Wenyuan Fang¹, Qiang Wei^{1, *}, Yuan Zhao¹, Liang Wang²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 273-295, 2020, DOI:10.32604/cmc.2020.09659

Abstract Code defects can lead to software vulnerability and even produce vulnerability risks. Existing research shows that the code detection technology with text analysis can judge whether object-oriented code files are defective to some extent. However, these detection techniques are mainly based on text features and have weak detection capabilities across programs. Compared with the uncertainty of the code and text caused by the developer’s personalization, the programming language has a stricter logical specification, which reflects the rules and requirements of the language itself and the developer’s potential way of thinking. This article replaces text analysis with programming logic modeling, breaks… More >

Xiaoyan Zhao^{1, *}, Shuwen Chen², Lin Zhou³, Ying Chen^{3, 4}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 253-271, 2020, DOI:10.32604/cmc.2020.09848

Abstract Microphone array-based sound source localization (SSL) is a challenging task in adverse acoustic scenarios. To address this, a novel SSL algorithm based on deep neural network (DNN) using steered response power-phase transform (SRP-PHAT) spatial spectrum as input feature is presented in this paper. Since the SRP-PHAT spatial power spectrum contains spatial location information, it is adopted as the input feature for sound source localization. DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features. SRP-PHAT at each steering position within a frame is arranged into a vector, which… More >

Shuqiang Guo^{1, *}, Baohai Yue¹, Manyang Gao², Xinxin Zhou¹, Bo Wang³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 233-251, 2020, DOI:10.32604/cmc.2020.010039

Abstract The recycling of glass bottles can reduce the consumption of resources and contribute to environmental protection. At present, the classification of recycled glass bottles is difficult due to the many differences in specifications and models. This paper proposes a classification algorithm for glass bottles that is divided into two stages, namely the extraction of candidate regions and the classification of classifiers. In the candidate region extraction stage, aiming at the problem of the large time overhead caused by the use of the SIFT (scale-invariant feature transform) descriptor in SS (selective search), an improved feature of HLSN (Haar-like based on SPP-Net)… More >

Wei Fang^{1, 2}, Feihong Zhang^{1, *}, Yewen Ding¹, Jack Sheng³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 217-231, 2020, DOI:10.32604/cmc.2020.06395

Abstract Image recognition technology is an important field of artificial intelligence. Combined with the development of machine learning technology in recent years, it has great researches value and commercial value. As a matter of fact, a single recognition function can no longer meet people’s needs, and accurate image prediction is the trend that people pursue. This paper is based on Long Short-Term Memory (LSTM) and Deep Convolution Generative Adversarial Networks (DCGAN), studies and implements a prediction model by using radar image data. We adopt a stack cascading strategy in designing network connection which can control of parameter convergence better. This new… More >

Yu Jiang^{1, 2}, Dengwen Yu¹, Mingzhao Zhao^{1, 2}, Hongtao Bai^{1, 2}, Chong Wang^{1, 2, 3}, Lili He^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 207-216, 2020, DOI:10.32604/cmc.2020.09861

Abstract Semi-supervised clustering improves learning performance as long as it uses a small number of labeled samples to assist un-tagged samples for learning. This paper implements and compares unsupervised and semi-supervised clustering analysis of BOAArgo ocean text data. Unsupervised K-Means and Affinity Propagation (AP) are two classical clustering algorithms. The Election-AP algorithm is proposed to handle the final cluster number in AP clustering as it has proved to be difficult to control in a suitable range. Semi-supervised samples thermocline data in the BOA-Argo dataset according to the thermocline standard definition, and use this data for semi-supervised cluster analysis. Several semi-supervised clustering… More >