A Privacy-Leakage-Tolerance Based Noise Enhancing Strategy for Privacy Protection in Cloud Computing

The Cloud computing paradigm can improve the efficiency of distributed computing by sharing resources and data over the Internet. However, the security levels of nodes (or severs) are not the same, thus, sensitive tasks and personal data may be scheduled (or shared) to some unsafe nodes, which can lead to privacy leakage. Traditional privacy preservation technologies focus on the protection of data release and process of communication, but lack protection against disposing sensitive tasks to untrusted computing nodes. Therefore, this article put forwards a protocol based on task-transformation, by which tasks will be transformed into another form in the task manager before they can be scheduled to other nodes. The article describes a privacy preservation algorithm based on separation sensitive attributes from values (SSAV) to realize the task-transformation function. This algorithm separates sensitive attributes in the tasks from their values, which make the malicious nodes cannot comprehend the real meaning of the values even they get the transformed tasks. Analysis and simulation results show that the authors' algorithm is more effective.

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A Blockchain-Based Location Privacy Protection Incentive Mechanism in Crowd Sensing Networks

Sensors ◽

10.3390/s18113894 ◽

2018 ◽

Vol 18 (11) ◽

pp. 3894 ◽

Cited By ~ 28

Author(s):

Bing Jia ◽

Tao Zhou ◽

Wuyungerile Li ◽

Zhenchang Liu ◽

Jiantao Zhang

Keyword(s):

Cloud Computing ◽

Privacy Protection ◽

Large Scale ◽

Location Privacy ◽

Incentive Mechanism ◽

User Participation ◽

Crowd Sensing ◽

The Incentive Mechanism ◽

Crowd Sensing Networks ◽

Location Privacy Protection

Crowd sensing is a perception mode that recruits mobile device users to complete tasks such as data collection and cloud computing. For the cloud computing platform, crowd sensing can not only enable users to collaborate to complete large-scale awareness tasks but also provide users for types, social attributes, and other information for the cloud platform. In order to improve the effectiveness of crowd sensing, many incentive mechanisms have been proposed. Common incentives are monetary reward, entertainment & gamification, social relation, and virtual credit. However, there are rare incentives based on privacy protection basically. In this paper, we proposed a mixed incentive mechanism which combined privacy protection and virtual credit called a blockchain-based location privacy protection incentive mechanism in crowd sensing networks. Its network structure can be divided into three parts which are intelligence crowd sensing networks, confusion mechanism, and blockchain. We conducted the experiments in the campus environment and the results shows that the incentive mechanism proposed in this paper has the efficacious effect in stimulating user participation.

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A Logistics Privacy Protection System Based on Cloud Computing

Lecture Notes in Electrical Engineering - Frontier Computing ◽

10.1007/978-981-10-3187-8_43 ◽

2017 ◽

pp. 455-461

Author(s):

Xin Liu ◽

Bingmeng Hu ◽

Qingguo Zhou ◽

Jingfeng Liu

Keyword(s):

Cloud Computing ◽

Privacy Protection ◽

Protection System

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A privacy protection approach for XML-based archives management in a cloud environment

The Electronic Library ◽

10.1108/el-05-2019-0127 ◽

2019 ◽

Vol 37 (6) ◽

pp. 970-983 ◽

Cited By ~ 1

Author(s):

Zongda Wu ◽

Jian Xie ◽

Xinze Lian ◽

Jun Pan

Keyword(s):

Cloud Computing ◽

Privacy Protection ◽

Design Methodology ◽

Digital Archive ◽

Cloud Environment ◽

System Availability ◽

Encrypted Data ◽

Content Type ◽

Main Obstacle ◽

Overall Performance

Purpose The security of archival privacy data in the cloud has become the main obstacle to the application of cloud computing in archives management. To this end, aiming at XML archives, this paper aims to present a privacy protection approach that can ensure the security of privacy data in the untrusted cloud, without compromising the system availability. Design/methodology/approach The basic idea of the approach is as follows. First, the privacy data before being submitted to the cloud should be strictly encrypted on a trusted client to ensure the security. Then, to query the encrypted data efficiently, the approach constructs some key feature data for the encrypted data, so that each XML query defined on the privacy data can be executed correctly in the cloud. Findings Finally, both theoretical analysis and experimental evaluation demonstrate the overall performance of the approach in terms of security, efficiency and accuracy. Originality/value This paper presents a valuable study attempting to protect privacy for the management of XML archives in a cloud environment, so it has a positive significance to promote the application of cloud computing in a digital archive system.

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A Cloud-User Protocol Based on Ciphertext Watermarking Technology

Security and Communication Networks ◽

10.1155/2017/4376282 ◽

2017 ◽

Vol 2017 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Keyang Liu ◽

Weiming Zhang ◽

Xiaojuan Dong

Keyword(s):

Cloud Computing ◽

Service Providers ◽

Hamming Distance ◽

Cloud Service ◽

Third Party ◽

Plain Text ◽

Privacy Leakage ◽

Cloud Computing Service ◽

The Right ◽

Cloud User

With the growth of cloud computing technology, more and more Cloud Service Providers (CSPs) begin to provide cloud computing service to users and ask for users’ permission of using their data to improve the quality of service (QoS). Since these data are stored in the form of plain text, they bring about users’ worry for the risk of privacy leakage. However, the existing watermark embedding and encryption technology is not suitable for protecting the Right to Be Forgotten. Hence, we propose a new Cloud-User protocol as a solution for plain text outsourcing problem. We only allow users and CSPs to embed the ciphertext watermark, which is generated and embedded by Trusted Third Party (TTP), into the ciphertext data for transferring. Then, the receiver decrypts it and obtains the watermarked data in plain text. In the arbitration stage, feature extraction and the identity of user will be used to identify the data. The fixed Hamming distance code can help raise the system’s capability for watermarks as much as possible. Extracted watermark can locate the unauthorized distributor and protect the right of honest CSP. The results of experiments demonstrate the security and validity of our protocol.

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