Ashwinth Janarthanan^1,*, Dhananjay Kumar¹

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 895-912, 2019, DOI:10.32604/cmc.2019.06805

Abstract Efficient aggregation in wireless sensor nodes helps reduce network traffic and reduce energy consumption. The objective of this work Localization Based Evolutionary Routing (LOBER) is to achieve global optimization for aggregation and WMSN lifetime. Improved localization is achieved by a novel Centroid Based Octant Localization (CBOL) technique considering an arbitrary hexagonal region. Geometric principles of hexagon are used to locate the unknown nodes in the centroid positions of partitioned regions. Flower pollination algorithm, a meta heuristic evolutionary algorithm that is extensively applied in solving real life, complex and nonlinear optimization problems in engineering and industry is modified as Enhanced Flower… More >

Jiyuan Liu¹, Yingzhi Zeng², Jiangyong Shi², Yuexiang Yang^2,∗, Rui Wang³, Liangzhong He⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 721-739, 2019, DOI:10.32604/cmc.2019.05610

Abstract Recently, TLS protocol has been widely used to secure the application data carried in network traffic. It becomes more difficult for attackers to decipher messages through capturing the traffic generated from communications of hosts. On the other hand, malwares adopt TLS protocol when accessing to internet, which makes most malware traffic detection methods, such as DPI (Deep Packet Inspection), ineffective. Some literatures use statistical method with extracting the observable data fields exposed in TLS connections to train machine learning classifiers so as to infer whether a traffic flow is malware or not. However, most of them adopt the features based… More >

M. Sivaram^1,*, D. Yuvaraj², Amin Salih Mohammed³, V. Manikandan⁴, V. Porkodi⁴, N. Yuvaraj⁵

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 435-454, 2019, DOI:10.32604/cmc.2019.06295

Abstract DBTMA relies entirely on RTS/CTS dialogue for un-collided transmission of data. The purpose is to improve the QoS at MAC layer by developing it over 802.11e standard. However, DBTMA does not guarantee real-time constraints without efficient method for controlling the network loads. The main challenges in MANETs include prediction of the available bandwidth, establishing communication with neighboring nodes and predicting the consumption of bandwidth flow. These challenges are provided with solutions using Contention-Aware Admission Control (CACP) protocol. In this paper, the EDBTMA protocol is combined with CACP protocol that introduces bandwidth calculation using admission control strategy. The calculation includes certain… More >

Yu Han^1,*, Wenxian Zheng², Guangjun Wen¹, Chu Chu¹, Jian Su³, Yibo Zhang⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 795-812, 2019, DOI:10.32604/cmc.2019.05719

Abstract In recent years, Researchers have proposed the concept of Energy Harvesting Backscatter Wireless Networks (EHBWN). EHBWN usually consists of one sink and several backscatter nodes. Backscatter nodes harvest energy from their environment and communicate with sink through backscattering the carrier wave transmitted by sink. Although a certain amount of access protocols for Energy Harvesting Wireless Networks have been present, they usually do not take the sink’s receiver sensitivity into account, which makes those protocols unsuitable in practice. In this paper, we first give an analysis of the backscatter channel link budget and the relationship between the effective communication range and… More >

Wei Xu^1,2, Yaodong Tao^2,3, Chunfang Yang^4,*, Huiqin Chen⁵

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 691-705, 2019, DOI:10.32604/cmc.2019.05678

Abstract A security testbed is an important aspect of Industrial Control System (ICS) security research. However, existing testbeds still have many problems in that they cannot fully simulate enterprise networks and ICS attacks. This paper presents a Multiple-Scenario Industrial Control System Testbed (MSICST), a hardware-in-the-loop ICS testbed for security research. The testbed contains four typical process scenarios: thermal power plant, rail transit, smart grid, and intelligent manufacturing. We use a combination of actual physical equipment and software simulations to build the process scenario sand table and use real hardware and software to build the control systems, demilitarized zone, and enterprise zone… More >

Sheng Bin^1,*, Gengxin Sun¹, Ning Cao², Jinming Qiu², Zhiyong Zheng³, Guohua Yang⁴, Hongyan Zhao⁵, Meng Jiang⁶, Lina Xu⁷

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 659-674, 2019, DOI:10.32604/cmc.2019.05858

Abstract Recommendation system is one of the most common applications in the field of big data. The traditional collaborative filtering recommendation algorithm is directly based on user-item rating matrix. However, when there are huge amounts of user and commodities data, the efficiency of the algorithm will be significantly reduced. Aiming at the problem, a collaborative filtering recommendation algorithm based on multi-relational social networks is proposed. The algorithm divides the multi-relational social networks based on the multi-subnet complex network model into communities by using information dissemination method, which divides the users with similar degree into a community. Then the user-item rating matrix… More >

Feng Xu¹, Xuefen Zhang^2,*, Zhanhong Xin¹, Alan Yang³

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 697-709, 2019, DOI:10.32604/cmc.2019.05375

Abstract Nowadays, the amount of wed data is increasing at a rapid speed, which presents a serious challenge to the web monitoring. Text sentiment analysis, an important research topic in the area of natural language processing, is a crucial task in the web monitoring area. The accuracy of traditional text sentiment analysis methods might be degraded in dealing with mass data. Deep learning is a hot research topic of the artificial intelligence in the recent years. By now, several research groups have studied the sentiment analysis of English texts using deep learning methods. In contrary, relatively few works have so far… More >

Jin Wang^1,2,3, Yu Gao³, Wei Liu³, Wenbing Wu¹, Se-Jung Lim^4,*

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 711-725, 2019, DOI:10.32604/cmc.2019.05450

Abstract Recently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of “hot spots” among sensors to enhance the lifetime of networks. The clustering process takes sensors’ location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with the data overflow time and… More >

Yecai Guo^1,2,*, Chen Li^1,2, Qi Liu³

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 829-843, 2019, DOI:10.32604/cmc.2019.03729

Abstract Visual degradation of captured images caused by rainy streaks under rainy weather can adversely affect the performance of many open-air vision systems. Hence, it is necessary to address the problem of eliminating rain streaks from the individual rainy image. In this work, a deep convolution neural network (CNN) based method is introduced, called Rain-Removal Net (R²N), to solve the single image de-raining issue. Firstly, we decomposed the rainy image into its high-frequency detail layer and low-frequency base layer. Then, we used the high-frequency detail layer to input the carefully designed CNN architecture to learn the mapping between it and its… More >

Min Long^1,2,*, Yan Zeng¹

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 493-504, 2019, DOI:10.32604/cmc.2019.04378

Abstract Aim to countermeasure the presentation attack for iris recognition system, an iris liveness detection scheme based on batch normalized convolutional neural network (BNCNN) is proposed to improve the reliability of the iris authentication system. The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris, including convolutional layer, batch-normalized (BN) layer, Relu layer, pooling layer and full connected layer. The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels, and then the iris features are extracted by BNCNN. With these features, the genuine iris and fake iris are determined by… More >