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  • Open Access

    ARTICLE

    Modelling the Roles of Cewebrity Trust and Platform Trust in Consumers’ Propensity of Live-Streaming: An Extended TAM Method

    Donghui Li1, Guozheng Zhang1,*, Zeng Xu1, Yong Lan1, Yongdong Shi2, Zhiyao Liang2, Haiwen Chen3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 137-150, 2018, DOI:10.3970/cmc.2018.055.137

    Abstract Live streaming is a booming industry in China, involving an increasing number of Internet users. Previous studies show that trust is a cornerstone to develop e-commerce. Trust in the streaming industry is different from that of other e-commerce areas. There are two major dimensions of trust in the live streaming context: platform trust and cewebrity trust, which are both important for customers to adopt and reuse a specific live streaming service. We collected questionnaire data from 520 participates who have used live streaming services in China. We model the collected data and identified factors that can influence users’ propensity by… More >

  • Open Access

    ARTICLE

    Adversarial Learning for Distant Supervised Relation Extraction

    Daojian Zeng1,3, Yuan Dai1,3, Feng Li1,3, R. Simon Sherratt2, Jin Wang3,*

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 121-136, 2018, DOI:10.3970/cmc.2018.055.121

    Abstract Recently, many researchers have concentrated on using neural networks to learn features for Distant Supervised Relation Extraction (DSRE). These approaches generally use a softmax classifier with cross-entropy loss, which inevitably brings the noise of artificial class NA into classification process. To address the shortcoming, the classifier with ranking loss is employed to DSRE. Uniformly randomly selecting a relation or heuristically selecting the highest score among all incorrect relations are two common methods for generating a negative class in the ranking loss function. However, the majority of the generated negative class can be easily discriminated from positive class and will contribute… More >

  • Open Access

    ARTICLE

    An Abnormal Network Flow Feature Sequence Prediction Approach for DDoS Attacks Detection in Big Data Environment

    Jieren Cheng1,2, Ruomeng Xu1,*, Xiangyan Tang1, Victor S. Sheng3, Canting Cai1

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 95-119, 2018, DOI:10.3970/cmc.2018.055.095

    Abstract Distributed denial-of-service (DDoS) is a rapidly growing problem with the fast development of the Internet. There are multitude DDoS detection approaches, however, three major problems about DDoS attack detection appear in the big data environment. Firstly, to shorten the respond time of the DDoS attack detector; secondly, to reduce the required compute resources; lastly, to achieve a high detection rate with low false alarm rate. In the paper, we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and solve aforementioned problems. We define… More >

  • Open Access

    ARTICLE

    Localization Algorithm of Indoor Wi-Fi Access Points Based on Signal Strength Relative Relationship and Region Division

    Wenyan Liu1, Xiangyang Luo1,*, Yimin Liu1, Jianqiang Liu2, Minghao Liu1, Yun Q. Shi3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 71-93, 2018, DOI:10.3970/cmc.2018.055.071

    Abstract Precise localization techniques for indoor Wi-Fi access points (APs) have important application in the security inspection. However, due to the interference of environment factors such as multipath propagation and NLOS (Non-Line-of-Sight), the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS (Received Signal Strength) is difficult to accurately measure. Therefore, the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper. The algorithm hierarchically divide the room where the target Wi-Fi AP is located, on the region… More >

  • Open Access

    ARTICLE

    Defining Embedding Distortion for Intra Prediction Mode-Based Video Steganography

    Qiankai Nie1, Xuba Xu1, Bingwen Feng1,*, Leo Yu Zhang2

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 59-70, 2018, DOI:10.3970/cmc.2018.055.059

    Abstract In this paper, an effective intra prediction mode-based video strganography is proposed. Secret messages are embedded during the intra prediction of the video encoding without causing large embedding impact. The influence on the sum of absolute difference (SAD) in intra prediction modes (IPMs) reversion phenomenon is sharp when modifying IPMs. It inspires us to take the SAD prediction deviation (SPD) to define the distortion function. What is more, the mapping rule between IPMs and the codewords is introduced to further reduce the SPD values of each intra block. Syndrome-trellis code (STC) is used as the practical embedding implementation. Experimental results… More >

  • Open Access

    ARTICLE

    Verifiable Diversity Ranking Search Over Encrypted Outsourced Data

    Yuling Liu1,*, Hua Peng1, Jie Wang2

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 37-57, 2018, DOI:10.3970/cmc.2018.055.037

    Abstract Data outsourcing has become an important application of cloud computing. Driven by the growing security demands of data outsourcing applications, sensitive data have to be encrypted before outsourcing. Therefore, how to properly encrypt data in a way that the encrypted and remotely stored data can still be queried has become a challenging issue. Searchable encryption scheme is proposed to allow users to search over encrypted data. However, most searchable encryption schemes do not consider search result diversification, resulting in information redundancy. In this paper, a verifiable diversity ranking search scheme over encrypted outsourced data is proposed while preserving privacy in… More >

  • Open Access

    ARTICLE

    Securing Display Path for Security-Sensitive Applications on Mobile Devices

    Jinhua Cui1,2, Yuanyuan Zhang3, Zhiping Cai1,*, Anfeng Liu4, Yangyang Li5

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 17-35, 2018, DOI:10.3970/cmc.2018.055.017

    Abstract While smart devices based on ARM processor bring us a lot of convenience, they also become an attractive target of cyber-attacks. The threat is exaggerated as commodity OSes usually have a large code base and suffer from various software vulnerabilities. Nowadays, adversaries prefer to steal sensitive data by leaking the content of display output by a security-sensitive application. A promising solution is to exploit the hardware visualization extensions provided by modern ARM processors to construct a secure display path between the applications and the display device. In this work, we present a scheme named SecDisplay for trusted display service, it… More >

  • Open Access

    ARTICLE

    A Fusion Steganographic Algorithm Based on Faster R-CNN

    Ruohan Meng1,2, Steven G. Rice3, Jin Wang4, Xingming Sun1,2,*

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 1-16, 2018, DOI:10.3970/cmc.2018.055.001

    Abstract The aim of information hiding is to embed the secret message in a normal cover media such as image, video, voice or text, and then the secret message is transmitted through the transmission of the cover media. The secret message should not be damaged on the process of the cover media. In order to ensure the invisibility of secret message, complex texture objects should be chosen for embedding information. In this paper, an approach which corresponds multiple steganographic algorithms to complex texture objects was presented for hiding secret message. Firstly, complex texture regions are selected based on a kind of… More >

  • Open Access

    ARTICLE

    Effect of Different Shapes of Conformal Cooling Channel on the Parameters of Injection Molding

    Mahesh S. Shinde1,*, Kishor M. Ashtankar1

    CMC-Computers, Materials & Continua, Vol.54, No.3, pp. 287-306, 2018, DOI:10.3970/cmc.2018.054.287

    Abstract Cooling system improvement is important in injection molding to get better quality and productivity. The aim of this paper was to compare the different shapes of the conformal cooling channels (CCC) with constant surface area and CCC with constant volume in injection molding using Mold-flow Insight 2016 software. Also the CCC results were compared with conventional cooling channels. Four different shapes of the CCC such as circular, elliptical, rectangular and semi-circular were proposed. The locations of the cooling channels were also kept constant. The results in terms of cooling time, cycle time reduction and improvement in quality of the product… More >

  • Open Access

    ARTICLE

    Time Optimization of Multiple Knowledge Transfers in the Big Data Environment

    Chuanrong Wu1, *, Evgeniya Zapevalova1, Yingwu Chen2, Feng Li3

    CMC-Computers, Materials & Continua, Vol.54, No.3, pp. 269-285, 2018, DOI:10.3970/cmc.2018.054.269

    Abstract In the big data environment, enterprises must constantly assimilate big data knowledge and private knowledge by multiple knowledge transfers to maintain their competitive advantage. The optimal time of knowledge transfer is one of the most important aspects to improve knowledge transfer efficiency. Based on the analysis of the complex characteristics of knowledge transfer in the big data environment, multiple knowledge transfers can be divided into two categories. One is the simultaneous transfer of various types of knowledge, and the other one is multiple knowledge transfers at different time points. Taking into consideration the influential factors, such as the knowledge type,… More >

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