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  • Open Access


    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


    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


    A Novel Privacy‐Preserving Multi‐Attribute Reverse Auction Scheme with Bidder Anonymity Using Multi‐Server Homomorphic Computation

    Wenbo Shi1, Jiaqi Wang2, Jinxiu Zhu3, YuPeng Wang4, Dongmin Choi5

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 171-181, 2019, DOI:10.31209/2018.100000053

    Abstract With the further development of Internet, the decision-making ability of the smart service is getting stronger and stronger, and the electronic auction is paid attention to as one of the ways of decision system. In this paper, a secure multi-attribute reverse auction protocol without the trusted third party is proposed. It uses the Paillier public key cryptosystem with homomorphism and combines with oblivious transfer and anonymization techniques. A single auction server easily collides with a bidder, in order to solve this problem, a single auction server is replaced with multiple auction servers. The proposed scheme uses multiple auction servers to… More >

  • Open Access


    Privacy-Preserving Decision Protocols Based on Quantum Oblivious Key Distribution

    Kejia Zhang1, 2, 3, 4, Chunguang Ma5, Zhiwei Sun4, 6, *, Xue Zhang2, 3, Baomin Zhou2, Yukun Wang7

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1915-1928, 2020, DOI:10.32604/cmc.2020.09836

    Abstract Oblivious key transfer (OKT) is a fundamental problem in the field of secure multi-party computation. It makes the provider send a secret key sequence to the user obliviously, i.e., the user may only get almost one bit key in the sequence which is unknown to the provider. Recently, a number of works have sought to establish the corresponding quantum oblivious key transfer model and rename it as quantum oblivious key distribution (QOKD) from the well-known expression of quantum key distribution (QKD). In this paper, a new QOKD model is firstly proposed for the provider and user with limited quantum capabilities,… More >

  • Open Access


    Privacy-Preserving Genetic Algorithm Outsourcing in Cloud Computing

    Leqi Jiang1, 2, Zhangjie Fu1, 2, *

    Journal of Cyber Security, Vol.2, No.1, pp. 49-61, 2020, DOI:10.32604/jcs.2020.09308

    Abstract Genetic Algorithm (GA) has been widely used to solve various optimization problems. As the solving process of GA requires large storage and computing resources, it is well motivated to outsource the solving process of GA to the cloud server. However, the algorithm user would never want his data to be disclosed to cloud server. Thus, it is necessary for the user to encrypt the data before transmitting them to the server. But the user will encounter a new problem. The arithmetic operations we are familiar with cannot work directly in the ciphertext domain. In this paper, a privacy-preserving outsourced genetic… More >

  • Open Access


    Achieving Privacy-Preserving Iris Identification Via El Gamal

    Yong Ding1, Lei Tian1, Bo Han2, Huiyong Wang2,*, Yujue Wang1, James Xi Zheng3

    CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 727-738, 2019, DOI:10.32604/cmc.2019.06220

    Abstract Currently, many biometric systems maintain the user’s biometrics and templates in plaintext format, which brings great privacy risk to uses’ biometric information. Biometrics are unique and almost unchangeable, which means it is a great concern for users on whether their biometric information would be leaked. To address this issue, this paper proposes a confidential comparison algorithm for iris feature vectors with masks, and develops a privacy-preserving iris verification scheme based on the El Gamal encryption scheme. In our scheme, the multiplicative homomorphism of encrypted features is used to compare of iris features and their mask information. Also, this paper improves… More >

  • Open Access


    Privacy-Preserving Content-Aware Search Based on Two-Level Index

    Zhangjie Fu1,*, Lili Xia1, Yuling Liu2, Zuwei Tian3

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 473-491, 2019, DOI:10.32604/cmc.2019.03785

    Abstract Nowadays, cloud computing is used more and more widely, more and more people prefer to using cloud server to store data. So, how to encrypt the data efficiently is an important problem. The search efficiency of existed search schemes decreases as the index increases. For solving this problem, we build the two-level index. Simultaneously, for improving the semantic information, the central word expansion is combined. The purpose of privacy-preserving content-aware search by using the two-level index (CKESS) is that the first matching is performed by using the extended central words, then calculate the similarity between the trapdoor and the secondary… More >

  • Open Access


    Reliable Medical Recommendation Based on Privacy-Preserving Collaborative Filtering

    Mengwei Hou1, Rong Wei1,*, Tiangang Wang1, Yu Cheng2, Buyue Qian3

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 137-149, 2018, DOI: 10.3970/cmc.2018.02438

    Abstract Collaborative filtering (CF) methods are widely adopted by existing medical recommendation systems, which can help clinicians perform their work by seeking and recommending appropriate medical advice. However, privacy issue arises in this process as sensitive patient private data are collected by the recommendation server. Recently proposed privacy-preserving collaborative filtering methods, using computation-intensive cryptography techniques or data perturbation techniques are not appropriate in medical online service. The aim of this study is to address the privacy issues in the context of neighborhood-based CF methods by proposing a Privacy Preserving Medical Recommendation (PPMR) algorithm, which can protect patients’ treatment information and demographic… More >

  • Open Access


    Privacy-Preserving Quantum Two-Party Geometric Intersection

    Wenjie Liu1,2,*, Yong Xu2, James C. N. Yang3, Wenbin Yu1,2, Lianhua Chi4

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1237-1250, 2019, DOI:10.32604/cmc.2019.03551

    Abstract Privacy-preserving computational geometry is the research area on the intersection of the domains of secure multi-party computation (SMC) and computational geometry. As an important field, the privacy-preserving geometric intersection (PGI) problem is when each of the multiple parties has a private geometric graph and seeks to determine whether their graphs intersect or not without revealing their private information. In this study, through representing Alice’s (Bob’s) private geometric graph GA (GB) as the set of numbered grids SA (SB), an efficient privacy-preserving quantum two-party geometric intersection (PQGI) protocol is proposed. In the protocol, the oracle operation OA (OB) is firstly utilized… More >

  • 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 comparing their underlying numerical values.… More >

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