Yuhang Wang¹, Yanbin Sun^1,*, Shen Su¹, Zhihong Tian¹, Mohan Li¹, Jing Qiu¹, Xianzhi Wang²

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 983-993, 2019, DOI:10.32604/cmc.2019.05547

Abstract With the evolution of location-based services (LBS), a new type of LBS has already gain a lot of attention and implementation, we name this kind of LBS as the Device-Dependent LBS (DLBS). In DLBS, the service provider (SP) will not only send the information according to the user’s location, more significant, he also provides a service device which will be carried by the user. DLBS has been successfully practised in some of the large cities around the world, for example, the shared bicycle in Beijing and London. In this paper, we, for the first time,… More >

Pingshui Wang^1,*, Zecheng Wang¹, Tao Chen^1,2, Qinjuan Ma¹

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 533-546, 2019, DOI:10.32604/cmc.2019.05570

Abstract With the rapid development of the new generation of information technology, the analysis of mobile social network big data is getting deeper and deeper. At the same time, the risk of privacy disclosure in social network is also very obvious. In this paper, we summarize the main access control model in mobile social network, analyze their contribution and point out their disadvantages. On this basis, a practical privacy policy is defined through authorization model supporting personalized privacy preferences. Experiments have been conducted on synthetic data sets. The result shows that the proposed privacy protecting model More >

Qiaoyang Zhang¹, Zhiyao Liang^1,*, Zhiping Cai²

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 457-471, 2019, DOI:10.32604/cmc.2019.03758

Abstract Wearable devices are becoming more popular in our daily life. They are usually used to monitor health status, track fitness data, or even do medical tests, etc. Since the wearable devices can obtain a lot of personal data, their security issues are very important. Motivated by the consideration that the current pairing mechanisms of Bluetooth Low Energy (BLE) are commonly impractical or insecure for many BLE based wearable devices nowadays, we design and implement a security framework in order to protect the communication between these devices. The security framework is a supplement to the Bluetooth… More >

Zhangjie Fu^1,*, 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 More >

Paolina Centonze^1,*

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 361-374, 2019, DOI:10.32604/cmc.2019.06223

Abstract In the security and privacy fields, Access Control (AC) systems are viewed as the fundamental aspects of networking security mechanisms. Enforcing AC becomes even more challenging when researchers and data analysts have to analyze complex and distributed Big Data (BD) processing cluster frameworks, which are adopted to manage yottabyte of unstructured sensitive data. For instance, Big Data systems’ privacy and security restrictions are most likely to failure due to the malformed AC policy configurations. Furthermore, BD systems were initially developed toped to take care of some of the DB issues to address BD challenges and… 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 >

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 >