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  • Open Access


    Enabling Comparable Search Over Encrypted Data for IoT with Privacy-Preserving

    Lei Xu1, Chungen Xu1,*, Zhongyi Liu1, Yunling Wang2,3, Jianfeng Wang2,3

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 675-690, 2019, DOI:10.32604/cmc.2019.05276

    Abstract With the rapid development of cloud computing and Internet of Things (IoT) technology, massive data raises and shuttles on the network every day. To ensure the confidentiality and utilization of these data, industries and companies users encrypt their data and store them in an outsourced party. However, simple adoption of encryption scheme makes the original lose its flexibility and utilization. To address these problems, the searchable encryption scheme is proposed. Different from traditional encrypted data search scheme, this paper focuses on providing a solution to search the data from one or more IoT device by… More >

  • Open Access


    A Privacy-Preserving Algorithm for Clinical Decision-Support Systems Using Random Forest

    Alia Alabdulkarim1, Mznah Al-Rodhaan2, Yuan Tian*,3, Abdullah Al-Dhelaan2

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 585-601, 2019, DOI:10.32604/cmc.2019.05637

    Abstract Clinical decision-support systems are technology-based tools that help healthcare providers enhance the quality of their services to satisfy their patients and earn their trust. These systems are used to improve physicians’ diagnostic processes in terms of speed and accuracy. Using data-mining techniques, a clinical decision support system builds a classification model from hospital’s dataset for diagnosing new patients using their symptoms. In this work, we propose a privacy-preserving clinical decision-support system that uses a privacy-preserving random forest algorithm to diagnose new symptoms without disclosing patients’ information and exposing them to cyber and network attacks. Solving More >

  • Open Access


    Differentially Private Real-Time Streaming Data Publication Based on Sliding Window Under Exponential Decay

    Lan Sun1, Chen Ge1, Xin Huang1, Yingjie Wu1,*, Yan Gao2

    CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 61-78, 2019, DOI:10.32604/cmc.2019.03744

    Abstract Continuous response of range query on steaming data provides useful information for many practical applications as well as the risk of privacy disclosure. The existing research on differential privacy streaming data publication mostly pay close attention to boosting query accuracy, but pay less attention to query efficiency, and ignore the effect of timeliness on data weight. In this paper, we propose an effective algorithm of differential privacy streaming data publication under exponential decay mode. Firstly, by introducing the Fenwick tree to divide and reorganize data items in the stream, we achieve a constant time complexity… More >

  • Open Access


    A Privacy-Preserving Image Retrieval Based on AC-Coefficients and Color Histograms in Cloud Environment

    Zhihua Xia1,*, Lihua Lu1, Tong Qiu1, H. J. Shim1, Xianyi Chen1, Byeungwoo Jeon2

    CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 27-43, 2019, DOI:10.32604/cmc.2019.02688

    Abstract Content based image retrieval (CBIR) techniques have been widely deployed in many applications for seeking the abundant information existed in images. Due to large amounts of storage and computational requirements of CBIR, outsourcing image search work to the cloud provider becomes a very attractive option for many owners with small devices. However, owing to the private content contained in images, directly outsourcing retrieval work to the cloud provider apparently bring about privacy problem, so the images should be protected carefully before outsourcing. This paper presents a secure retrieval scheme for the encrypted images in the… More >

  • Open Access


    Expression Preserved Face Privacy Protection Based on Multi-mode Discriminant Analysis

    Xiang Wang1, *, Chen Xiong1, Qingqi Pei1, Youyang Qu2

    CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 107-121, 2018, DOI:10.32604/cmc.2018.03675

    Abstract Most visual privacy protection methods only hide the identity information of the face images, but the expression, behavior and some other information, which are of great significant in the live broadcast and other scenarios, are also destroyed by the privacy protection process. To this end, this paper introduces a method to remove the identity information while preserving the expression information by performing multi-mode discriminant analysis on the images normalized with AAM algorithm. The face images are decomposed into mutually orthogonal subspaces corresponding to face attributes such as gender, race and expression, each of which owns More >

  • Open Access


    On the Privacy-Preserving Outsourcing Scheme of Reversible Data Hiding over Encrypted Image Data in Cloud Computing

    Lizhi Xiong1,*, Yunqing Shi2

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 523-539, 2018, DOI: 10.3970/cmc.2018.01791

    Abstract Advanced cloud computing technology provides cost saving and flexibility of services for users. With the explosion of multimedia data, more and more data owners would outsource their personal multimedia data on the cloud. In the meantime, some computationally expensive tasks are also undertaken by cloud servers. However, the outsourced multimedia data and its applications may reveal the data owner’s private information because the data owners lose the control of their data. Recently, this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data. In this paper, two reversible data hiding… More >

  • Open Access


    Inverted XML Access Control Model Based on Ontology Semantic Dependency

    Meijuan Wang1,2,*, Jian Wang1, Lihong Guo1,3, Lein Harn4

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 465-482, 2018, DOI: 10.3970/cmc.2018.02568

    Abstract In the era of big data, the conflict between data mining and data privacy protection is increasing day by day. Traditional information security focuses on protecting the security of attribute values without semantic association. The data privacy of big data is mainly reflected in the effective use of data without exposing the user’s sensitive information. Considering the semantic association, reasonable security access for privacy protect is required. Semi-structured and self-descriptive XML (eXtensible Markup Language) has become a common form of data organization for database management in big data environments. Based on the semantic integration nature More >

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