Privacy-Preserving Crowd-Sourced Statistical Data Publishing with An Untrusted Server

Wang, Zhen; Pang, Xiaoyi; Chen, Yahong; Shao, Hu; Wang, Qian; Wu, Libing; Chen, Honglong; Qi, Hairong

doi:10.1109/tmc.2018.2861765

Cited by 110 publications

(43 citation statements)

References 22 publications

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“…Leveraging agents is also considered to cope with the untrusted nature of MCS servers. With this in mind, the authors of Reference [77] propose a distributed agent-based strategy to ensure a certain level of privacy where crowd-sourced data goes through every agent following perturbation of aggregated statistics at the agents.…”

Section: Agent-based Strategiesmentioning

confidence: 99%

Game Theory in Mobile CrowdSensing: A Comprehensive Survey

Dasari

Kantarcı

Pouryazdan³

et al. 2020

Sensors

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Mobile CrowdSensing (MCS) is an emerging paradigm in the distributed acquisition of smart city and Internet of Things (IoT) data. MCS requires large number of users to enable access to the built-in sensors in their mobile devices and share sensed data to ensure high value and high veracity of big sensed data. Improving user participation in MCS campaigns requires to boost users effectively, which is a key concern for the success of MCS platforms. As MCS builds on non-dedicated sensors, data trustworthiness cannot be guaranteed as every user attains an individual strategy to benefit from participation. At the same time, MCS platforms endeavor to acquire highly dependable crowd-sensed data at lower cost. This phenomenon introduces a game between users that form the participant pool, as well as between the participant pool and the MCS platform. Research on various game theoretic approaches aims to provide a stable solution to this problem. This article presents a comprehensive review of different game theoretic solutions that address the following issues in MCS such as sensing cost, quality of data, optimal price determination between data requesters and providers, and incentives. We propose a taxonomy of game theory-based solutions for MCS platforms in which problems are mainly formulated based on Stackelberg, Bayesian and Evolutionary games. We present the methods used by each game to reach an equilibrium where the solution for the problem ensures that every participant of the game is satisfied with their utility with no requirement of change in their strategies. The initial criterion to categorize the game theoretic solutions for MCS is based on co-operation and information available among participants whereas a participant could be either a requester or provider. Following a thorough qualitative comparison of the surveyed approaches, we provide insights concerning open areas and possible directions in this active field of research.

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Section: Agent-based Strategiesmentioning

confidence: 99%

Game Theory in Mobile CrowdSensing: A Comprehensive Survey

Dasari

Kantarcı

Pouryazdan³

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Many existing systems depend on the trusted server to collect the spatio-temporal crowd data [56] to disturb the collective statistics by using differential privacy mechanism in order to provide strong privacy. If the server gets hacked the privacy of users will be revealed.…”

Section: Measures For Security Specific To Untrusted Server and Imagementioning

confidence: 99%

“…Distributed agent-based privacy-preserving framework Privacy preservation for Untrusted Server [56] Identity-based Encryption Security [57] Grouper framework without trusted central servers Security [58] Privacy preserving SIFT Image Feature Extraction with Privacy preservation [59] Securing SIFT Image Feature Extraction with Privacy preservation [60]…”

Section: Proposed Work Focus Referencesmentioning

confidence: 99%

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An Exhaustive Review on Security Issues in Cloud Computing

Fatima¹,

Ahmad²

2019

KSII TIIS

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The Cloud Computing is growing rapidly in the current IT industry. Cloud computing has become a buzzword in relation to Grid & Utility computing. It provides on demand services to customers and customers will pay for what they get. Various "Cloud Service Provider" such as Microsoft Azure, Google Web Services etc. enables the users to access the cloud in cost effective manner. However, security, privacy and integrity of data is a major concern. In this paper various security challenges have been identified and the survey briefs the comprehensive overview of various security issues in cloud computing. The classification of security issues in cloud computing have been studied. In this paper we have discussed security challenges in cloud computing and also list recommended methods available for addressing them in the literature.

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“…Due to the broadcast nature, signals from any transmitter are shared by all access receivers, which means interference channels are exposed to security risks of eavesdropping attacks. Traditionally, secure communications are achieved by using encryption algorithms [2][3]. However, with the rapid development of computing speed, once quantum computers are put into practice, traditional cryptography will be greatly challenged by brute force of quantum computing.…”

Section: Introductionmentioning

confidence: 99%

A Cooperative Jamming Based Joint Transceiver Design for Secure Communications in MIMO Interference Channels

2019

KSII TIIS

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In this paper, we investigate the problem of secure communications in multiple-input-multiple-output interference networks from the perspective of physical layer security. Specifically, the legitimate transmitter-receiver pairs are divided into different categories of active and inactive. To enhance the security performances of active pairs, inactive pairs serve as cooperative jammers and broadcast artificial noises to interfere with the eavesdropper. Besides, active pairs improve their own security by using joint transceivers. The encoding of active pairs and inactive pairs are designed by maximizing the difference of mean-squared errors between active pairs and the eavesdropper. In detail, the transmit precoder matrices of active pairs and inactive pairs are solved according to game theory and linear programming respectively. Experimental results show that the proposed algorithm has fast convergence speed, and the security performances in different scenarios are effectively improved.

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Privacy-Preserving Crowd-Sourced Statistical Data Publishing with An Untrusted Server

Cited by 110 publications

References 22 publications

Game Theory in Mobile CrowdSensing: A Comprehensive Survey

Game Theory in Mobile CrowdSensing: A Comprehensive Survey

An Exhaustive Review on Security Issues in Cloud Computing

A Cooperative Jamming Based Joint Transceiver Design for Secure Communications in MIMO Interference Channels

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