Privacy-Preserving Collaborative Path Hiding for Participatory Sensing Applications

2011 ◽  
Author(s):  
Delphine Christin ◽  
Julien Guillemet ◽  
Andreas Reinhardt ◽  
Matthias Hollick ◽  
Salil S. Kanhere
Keyword(s):  
Privacy Preserving ◽  
Participatory Sensing ◽  
Sensing Applications

scholarly journals A Privacy-Preserving Incentive Mechanism for Participatory Sensing Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xiaoguang Niu ◽  
Jiawei Wang ◽  
Qiongzan Ye ◽  
Yihao Zhang
Keyword(s):  
Dynamic Balance ◽  
Incentive Mechanism ◽  
Privacy Preserving ◽  
Circulation System ◽  
Participatory Sensing ◽  
Sensing Systems ◽  
Sensing Applications ◽  
Ideal Situation ◽  
Conflicting Objectives ◽  
Share Information

The proliferation of mobile devices has facilitated the prevalence of participatory sensing applications in which participants collect and share information in their environments. The design of a participatory sensing application confronts two challenges: “privacy” and “incentive” which are two conflicting objectives and deserve deeper attention. Inspired by physical currency circulation system, this paper introduces the notion of E-cent, an exchangeable unit bearer currency. Participants can use the E-cent to take part in tasks anonymously. By employing E-cent, we propose an E-cent-based privacy-preserving incentive mechanism, called EPPI. As a dynamic balance regulatory mechanism, EPPI can not only protect the privacy of participant, but also adjust the whole system to the ideal situation, under which the rated tasks can be finished at minimal cost. To the best of our knowledge, EPPI is the first attempt to build an incentive mechanism while maintaining the desired privacy in participatory sensing systems. Extensive simulation and analysis results show that EPPI can achieve high anonymity level and remarkable incentive effects.

scholarly journals A privacy-preserving collaborative reputation system for mobile crowdsensing

2018 ◽  
Vol 14 (9) ◽  
pp. 155014771880218 ◽  
Author(s):  
Bayan Hashr Alamri ◽  
Muhammad Mostafa Monowar ◽  
Suhair Alshehri
Keyword(s):  
Security Analysis ◽  
Privacy Preserving ◽  
Reputation System ◽  
Mobile Crowdsensing ◽  
Sensing Applications ◽  
Conflicting Objectives ◽  
Trusted Data ◽  
Privacy Issues ◽  
Open Nature

Mobile crowdsensing is an emerging technology in which participants contribute sensor readings for different sensing applications. This technology enables a broad range of sensing applications by utilizing smartphones and tablets worldwide to improve people’s quality of life. Protecting participants’ privacy and ensuring the trustworthiness of the sensor readings are conflicting objectives and key challenges in this field. Privacy issues arise from the disclosure of the participant-related context information, such as participants’ location. Trustworthiness issues arise from the open nature of sensing system because anyone can contribute data. This article proposes a privacy-preserving collaborative reputation system that preserves privacy and ensures data trustworthiness of the sensor readings for mobile crowdsensing applications. The proposed work also counters a number of possible attacks that might occur in mobile crowdsensing applications. We provide a detailed security analysis to prove the effectiveness of privacy-preserving collaborative reputation system against a number of attacks. We conduct an extensive simulation to investigate the performance of our schema. The obtained results show that the proposed schema is practical; it succeeds in identifying malicious users in most scenarios. In addition, it tolerates a large number of colluding adversaries even if their number surpass 65%. Moreover, it detects on-off attackers even if they report trusted data with high probability (0.8).

scholarly journals Self-organising management of user-generated data and knowledge

2014 ◽  
Vol 30 (3) ◽  
pp. 237-264 ◽  
Author(s):  
Sam Macbeth ◽  
Jeremy V. Pitt
Keyword(s):  
Pervasive Computing ◽  
User Generated Content ◽  
Participatory Sensing ◽  
Open Approach ◽  
Computational Logic ◽  
New Class ◽  
Sensing Applications ◽  
Development Framework ◽  
Governance Model ◽  
Institutional Analysis And Development

AbstractThe proliferation of sensor networks, mobile and pervasive computing has provided the technological push for a new class of participatory-sensing applications, based on sensing and aggregating user-generated content, and transforming it into knowledge. However, given the power and value of both the raw data and the derived knowledge, to ensure that the generators are commensurate beneficiaries, we advocate an open approach to the data and intellectual property rights by treating user-generated content, as well as derived information and knowledge, as a common-pool resource. In this paper, we undertake an extensive review of experimental, commercial and social participatory sensory applications, from which we identify that a decentralised, community-oriented governance model is required to support this approach. Furthermore, we show that Ostrom’s institutional analysis and development framework, in conjunction with a framework for self-organising electronic institutions, can be used to give both an architecture and algorithmic base for the requisite governance model, in terms of operational and collective-choice rules specified in computational logic. This provides, we believe, the foundations for engineering knowledge commons for the next generation of participatory-sensing applications, in which the data generators are also the primary beneficiaries.

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