Location-privacy-aware review publication mechanism for local business service systems

Zheng, Xu; Cai, Zhipeng; Li, Jianzhong; Gao, Hong

doi:10.1109/infocom.2017.8056976

Cited by 115 publications

(78 citation statements)

References 21 publications

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“…For example, whether two individuals in a social network have a close relationship may be expected to be kept a secret. Therefore, privacy concerns have been raised in increasingly emerging technologies [2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

An Edge Correlation Based Differentially Private Network Data Release Method

Cai

Wang

et al. 2017

Security and Communication Networks

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Differential privacy (DP) provides a rigorous and provable privacy guarantee and assumes adversaries' arbitrary background knowledge, which makes it distinct from prior work in privacy preserving. However, DP cannot achieve claimed privacy guarantees over datasets with correlated tuples. Aiming to protect whether two individuals have a close relationship in a correlated dataset corresponding to a weighted network, we propose a differentially private network data release method, based on edge correlation, to gain the tradeoff between privacy and utility. Specifically, we first extracted the Edge Profile (PF) of an edge from a graph, which is transformed from a raw correlated dataset. Then, edge correlation is defined based on the PFs of both edges via JensonShannon Divergence (JS-Divergence). Secondly, we transform a raw weighted dataset into an indicated dataset by adopting a weight threshold, to satisfy specific real need and decrease query sensitivity. Furthermore, we propose -correlated edge differential privacy (CEDP), by combining the correlation analysis and the correlated parameter with traditional DP. Finally, we propose network data release (NDR) algorithm based on the -CEDP model and discuss its privacy and utility. Extensive experiments over real and synthetic network datasets show the proposed releasing method provides better utilities while maintaining privacy guarantee.

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Section: Introductionmentioning

confidence: 99%

An Edge Correlation Based Differentially Private Network Data Release Method

Cai

Wang

et al. 2017

Security and Communication Networks

Self Cite

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“…Multicast authentication schemes such as TELSA, Biba, HORS, and OTS [3,23] were proposed for authenticating entities such as utility companies and control centers when messages or control commands are sent to smart meters. To authenticate smart meters or other smart devices to the control center, batch verification schemes [24][25][26][27] were developed to improve the efficiency. Data aggregation based on homomorphic encryption, secret sharing, and other technologies [13,25,26] was designed to aggregate customers' data and to protect their privacy.…”

Section: Related Workmentioning

confidence: 99%

A Secure and Scalable Data Communication Scheme in Smart Grids

Liu

et al. 2018

Wireless Communications and Mobile Computing

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The concept of smart grid gained tremendous attention among researchers and utility providers in recent years. How to establish a secure communication among smart meters, utility companies, and the service providers is a challenging issue. In this paper, we present a communication architecture for smart grids and propose a scheme to guarantee the security and privacy of data communications among smart meters, utility companies, and data repositories by employing decentralized attribute based encryption. The architecture is highly scalable, which employs an access control Linear Secret Sharing Scheme (LSSS) matrix to achieve a role-based access control. The security analysis demonstrated that the scheme ensures security and privacy. The performance analysis shows that the scheme is efficient in terms of computational cost.

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“…Even more, due to the complexity and diversity of fog nodes, user privacy in a fog network can easily be disclosure. For example, more than 400, 000 electronic eyes in Beijing may lead to privacy leakage (e.g., vehicle location information) by data sharing in vehicular ad hoc networks (VANETs) [6][7][8]. Similarly, we can also gain illegal access to personal health datasets gathered from various sensors of physical sign in body sensor networks (BSNs) and publish these private data without permission [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Re-ADP: Real-Time Data Aggregation with Adaptive ω-Event Differential Privacy for Fog Computing

Huo

Yong

2018

Wireless Communications and Mobile Computing

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In the Internet of Things (IoT), aggregation and release of real-time data can often be used for mining more useful information so as to make humans lives more convenient and efficient. However, privacy disclosure is one of the most concerning issues because sensitive information usually comes with users in aggregated data. Thus, various data encryption technologies have emerged to achieve privacy preserving. These technologies may not only introduce complicated computing and high communication overhead but also do not work on the protection of endless data streams. Considering these challenges, we propose a real-time stream data aggregation framework with adaptive -event differential privacy (Re-ADP). Based on adaptive -event differential privacy, the framework can protect any data collected by sensors over any dynamic time stamp successively over infinite stream. It is designed for the fog computing architecture that dramatically extends the cloud computing to the edge of networks. In our proposed framework, fog servers will only send aggregated secure data to cloud servers, which can relieve the computing overhead of cloud servers, improve communication efficiency, and protect data privacy. Finally, experimental results demonstrate that our framework outperforms the existing methods and improves data availability with stronger privacy preserving.

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Location-privacy-aware review publication mechanism for local business service systems

Cited by 115 publications

References 21 publications

An Edge Correlation Based Differentially Private Network Data Release Method

An Edge Correlation Based Differentially Private Network Data Release Method

A Secure and Scalable Data Communication Scheme in Smart Grids

Re-ADP: Real-Time Data Aggregation with Adaptive ω-Event Differential Privacy for Fog Computing

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