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Search Results (208)
  • Open Access

    ARTICLE

    Blockchain Data Privacy Access Control Based on Searchable Attribute Encryption

    Tao Feng1,*, Hongmei Pei1, Rong Ma1, Youliang Tian2, Xiaoqin Feng3

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 871-890, 2021, DOI:10.32604/cmc.2020.012146

    Abstract Data privacy is important to the security of our society, and enabling authorized users to query this data efficiently is facing more challenge. Recently, blockchain has gained extensive attention with its prominent characteristics as public, distributed, decentration and chronological characteristics. However, the transaction information on the blockchain is open to all nodes, the transaction information update operation is even more transparent. And the leakage of transaction information will cause huge losses to the transaction party. In response to these problems, this paper combines hierarchical attribute encryption with linear secret sharing, and proposes a blockchain data privacy protection control scheme based… More >

  • Open Access

    ARTICLE

    Privacy-Preserving Recommendation Based on Kernel Method in Cloud Computing

    Tao Li1, Qi Qian2, Yongjun Ren3,*, Yongzhen Ren4, Jinyue Xia5

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 779-791, 2021, DOI:10.32604/cmc.2020.010424

    Abstract The application field of the Internet of Things (IoT) involves all aspects, and its application in the fields of industry, agriculture, environment, transportation, logistics, security and other infrastructure has effectively promoted the intelligent development of these aspects. Although the IoT has gradually grown in recent years, there are still many problems that need to be overcome in terms of technology, management, cost, policy, and security. We need to constantly weigh the benefits of trusting IoT products and the risk of leaking private data. To avoid the leakage and loss of various user data, this paper developed a hybrid algorithm of… More >

  • Open Access

    ARTICLE

    A Framework for Systematic Classification of Assets for Security Testing

    Sadeeq Jan1,*, Omer Bin Tauqeer1, Fazal Qudus Khan2, George Tsaramirsis2, Awais Ahmad3, Iftikhar Ahmad4, Imran Maqsood5, Niamat Ullah6

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 631-645, 2021, DOI:10.32604/cmc.2020.012831

    Abstract Over the last decade, a significant increase has been observed in the use of web-based Information systems that process sensitive information, e.g., personal, financial, medical. With this increased use, the security of such systems became a crucial aspect to ensure safety, integrity and authenticity of the data. To achieve the objectives of data safety, security testing is performed. However, with growth and diversity of information systems, it is challenging to apply security testing for each and every system. Therefore, it is important to classify the assets based on their required level of security using an appropriate technique. In this paper,… More >

  • Open Access

    ARTICLE

    Secure and Efficient Data Storage and Sharing Scheme Based on Double Blockchain

    Lejun Zhang1,2,*, Minghui Peng1, Weizheng Wang3 , Yansen Su4, Shuna Cui5,6, Seokhoon Kim7

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 499-515, 2021, DOI:10.32604/cmc.2020.012205

    Abstract In the digital era, electronic medical record (EMR) has been a major way for hospitals to store patients’ medical data. The traditional centralized medical system and semi-trusted cloud storage are difficult to achieve dynamic balance between privacy protection and data sharing. The storage capacity of blockchain is limited and single blockchain schemes have poor scalability and low throughput. To address these issues, we propose a secure and efficient medical data storage and sharing scheme based on double blockchain. In our scheme, we encrypt the original EMR and store it in the cloud. The storage blockchain stores the index of the… More >

  • Open Access

    ARTICLE

    A Differential Privacy Based (k-Ψ)-Anonymity Method for Trajectory Data Publishing

    Hongyu Chen1, Shuyu Li1, *, Zhaosheng Zhang1

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2665-2685, 2020, DOI:10.32604/cmc.2020.010965

    Abstract In recent years, mobile Internet technology and location based services have wide application. Application providers and users have accumulated huge amount of trajectory data. While publishing and analyzing user trajectory data have brought great convenience for people, the disclosure risks of user privacy caused by the trajectory data publishing are also becoming more and more prominent. Traditional k-anonymous trajectory data publishing technologies cannot effectively protect user privacy against attackers with strong background knowledge. For privacy preserving trajectory data publishing, we propose a differential privacy based (k-Ψ)-anonymity method to defend against re-identification and probabilistic inference attack. The proposed method is divided… More >

  • Open Access

    ARTICLE

    Lightweight Mobile Clients Privacy Protection Using Trusted Execution Environments for Blockchain

    Jieren Cheng1, Jun Li2, *, Naixue Xiong3, Meizhu Chen2, Hao Guo2, Xinzhi Yao2

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2247-2262, 2020, DOI:10.32604/cmc.2020.011668

    Abstract Nowadays, as lightweight mobile clients become more powerful and widely used, more and more information is stored on lightweight mobile clients, user sensitive data privacy protection has become an urgent concern and problem to be solved. There has been a corresponding rise of security solutions proposed by researchers, however, the current security mechanisms on lightweight mobile clients are proven to be fragile. Due to the fact that this research field is immature and still unexplored in-depth, with this paper, we aim to provide a structured and comprehensive study on privacy protection using trusted execution environment (TEE) for lightweight mobile clients.… More >

  • Open Access

    ARTICLE

    Image Feature Computation in Encrypted Domain Based on Mean Value

    Xiangshu Ou1, Mingfang Jiang2,*, Shuai Li1, Yao Bai1

    Journal of Cyber Security, Vol.2, No.3, pp. 123-130, 2020, DOI:10.32604/jcs.2020.09703

    Abstract In smart environments, more and more teaching data sources are uploaded to remote cloud centers which promote the development of the smart campus. The outsourcing of massive teaching data can reduce storage burden and computational cost, but causes some privacy concerns because those teaching data (especially personal image data) may contain personal private information. In this paper, a privacy-preserving image feature extraction algorithm is proposed by using mean value features. Clients use block scrambling and chaotic map to encrypt original images before uploading to the remote servers. Cloud servers can directly extract image mean value features from encrypted images. Experiments… More >

  • Open Access

    ARTICLE

    A Proposal for Addressing Security Issues Related to Dynamic Code Loading on Android Platform

    Aleksandar Kelec, Zoran Djuric

    Computer Systems Science and Engineering, Vol.35, No.4, pp. 271-282, 2020, DOI:10.32604/csse.2020.35.271

    Abstract One of the constant challenges faced by the Android community, when it comes to the safety of the end users, is the ability of applications to load code dynamically. This mechanism may be used for both legitimate and malicious purposes. A particular problem is the fact that remote code is not analyzed during the verification process because it doesn’t have to be present in the application package at the publishing time. Previous research has shown that using this concept in an insecure way can cause serious consequences for the user and his device. Solving this problem has proved to be… More >

  • Open Access

    ARTICLE

    The Impact of Privacy Seal on Users’ Perception in Network Transactions

    Jing Chen,Yuchen Luo2,†, Ruiqi Du3,‡

    Computer Systems Science and Engineering, Vol.35, No.3, pp. 199-206, 2020, DOI:10.32604/csse.2020.35.199

    Abstract In the age of big data, the issue of online privacy has attracted much attention from all sectors. The introduction and establishment of an evaluation system for the privacy agreement based on a third party, together with the establishment of a safer internet transaction environment, can help to establish mutual trust between users and the platform. With the research background links to the online trading platform, this article investigates how the privacy seal which is provided by the third-party evaluation organization influences and addresses trust-awareness and privacy concerns of users, as well as exposing information and purchasing data. According to… More >

  • Open Access

    ARTICLE

    An Efficient Supervised Energy Disaggregation Scheme for Power Service in Smart Grid

    Weilie Liu, Jialing He, Meng Li, Rui Jin, Jingjing Hu, Zijian Zhang

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 585-593, 2019, DOI:10.31209/2019.100000113

    Abstract Smart energy disaggregation is receiving increasing attention because it can be used to save energy and mine consumer's electricity privacy by decomposing aggregated meter readings. Many smart energy disaggregation schemes have been proposed; however, the accuracy and efficiency of these methods need to be improved. In this work, we consider a supervised energy disaggregation method which initially learns the power consumption of each appliance and then disaggregates meter readings using the previous learning result. In this study, we improved the fast search and find of density peaks clustering algorithm to cluster appliance power signals twice to learn appliance feature matrices.… More >

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