scholarly journals A Privacy-Preserving Identification Mechanism for Mobile Sensing Systems

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 15457-15467 ◽  
Author(s):  
Xiaoguang Niu ◽  
Qiongzan Ye ◽  
Yihao Zhang ◽  
Dengpan Ye
Keyword(s):  
Privacy Preserving ◽  
Mobile Sensing ◽  
Sensing Systems ◽  
Identification Mechanism

Efficient location privacy-preserving range query scheme for vehicle sensing systems

2020 ◽  
Vol 106 ◽  
pp. 101714 ◽  
Author(s):  
Peng Hu ◽  
Yongli Wang ◽  
Quanbing Li ◽  
Yongjian Wang ◽  
Yanchao Li ◽  
...  
Keyword(s):  
Location Privacy ◽  
Range Query ◽  
Privacy Preserving ◽  
Sensing Systems

scholarly journals Privacy Leakage in Mobile Sensing: Your Unlock Passwords Can Be Leaked through Wireless Hotspot Functionality

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Jie Zhang ◽  
Xiaolong Zheng ◽  
Zhanyong Tang ◽  
Tianzhang Xing ◽  
Xiaojiang Chen ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Mobile Sensing ◽  
Experimental Results ◽  
Smart Devices ◽  
Detection Accuracy ◽  
Phase Information ◽  
Current Sensing ◽  
Privacy Leakage ◽  
Sensing Systems ◽  
Additional Hardware

Mobile sensing has become a new style of applications and most of the smart devices are equipped with varieties of sensors or functionalities to enhance sensing capabilities. Current sensing systems concentrate on how to enhance sensing capabilities; however, the sensors or functionalities may lead to the leakage of users’ privacy. In this paper, we present WiPass, a way to leverage the wireless hotspot functionality on the smart devices to snoop the unlock passwords/patterns without the support of additional hardware. The attacker can “see” your unlock passwords/patterns even one meter away. WiPass leverages the impacts of finger motions on the wireless signals during the unlocking period to analyze the passwords/patterns. To practically implement WiPass, we are facing the difficult feature extraction and complex unlock passwords matching, making the analysis of the finger motions challenging. To conquer the challenges, we use DCASW to extract feature and hierarchical DTW to do unlock passwords matching. Besides, the combination of amplitude and phase information is used to accurately recognize the passwords/patterns. We implement a prototype of WiPass and evaluate its performance under various environments. The experimental results show that WiPass achieves the detection accuracy of 85.6% and 74.7% for passwords/patterns detection in LOS and in NLOS scenarios, respectively.

Enabling reputation and trust in privacy-preserving mobile sensing

2014 ◽  
Vol 13 (12) ◽  
pp. 2777-2790 ◽  
Author(s):  
Xinlei Wang ◽  
Wei Cheng ◽  
Prasant Mohapatra ◽  
Tarek Abdelzaher
Keyword(s):  
Privacy Preserving ◽  
Mobile Sensing

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.

A multi-agent architecture for mobile sensing systems

2019 ◽  
Vol 11 (11) ◽  
pp. 4439-4451 ◽  
Author(s):  
Francisco Laport ◽  
Emilio Serrano ◽  
Javier Bajo
Keyword(s):  
Mobile Sensing ◽  
Agent Architecture ◽  
Sensing Systems ◽  
Multi Agent
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