Yuanyuan Xu^1,*, Shan Li², Yixuan Zhang³

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 129-139, 2019, DOI:10.32604/cmc.2019.05691

Abstract With the emergence of ambient sensing technologies which combine mobile crowdsensing and Internet of Things, large amount of people-centric data can be obtained and utilized to build people-centric services. Note that the service quality is highly related to the privacy level of the data. In this paper, we investigate the problem of privacy-aware service subscription in people-centric sensing. An efficient resource allocation framework using a combinatorial auction (CA) model is provided. Specifically, the resource allocation problem that maximizes the social welfare in view of varying requirements of multiple users is formulated, and it is solved More >

Wenjie Liu^1,2,*, Yong Xu², James C. N. Yang³, Wenbin Yu^1,2, 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 G_A (G_B) as the set of numbered grids S_A (S_B), an efficient privacy-preserving quantum two-party geometric intersection (PQGI) protocol is proposed. In the protocol, the oracle operation O_A (O_B) is More >

Lei Xu¹, Chungen Xu^1,*, Zhongyi Liu¹, Yunling Wang^2,3, Jianfeng Wang^2,3

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 >

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 >

Lan Sun¹, Chen Ge¹, Xin Huang¹, Yingjie Wu^1,*, 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 >

Zhihua Xia^1,*, 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 >

Mengwei Hou¹, Rong Wei^1,*, 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… More >

Xiang Wang^{1, *}, 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 >

Lizhi Xiong^1,*, 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 >

Meijuan Wang^1,2,*, Jian Wang¹, Lihong Guo^1,3, 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 >