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Enhancing Sparse Mobile CrowdSensing With Manifold Optimization and Differential Privacy
IEEE Transactions on Information Forensics and SecuritySparse Mobile CrowdSensing (SMCS) effectively lowers sensing costs while maintaining data quality, offering an alternative approach to data collection. Unfortunately, the fact that data contain sensitive information raises serious privacy concerns. Local
Chengxin Li +5 more
semanticscholar +1 more source
IEEE Internet of Things Journal
Emerging crowdsensing paradigm enables a large number of sensing applications, where much attention is drawn to the fundamental problems for maximizing the system utility and improving the data quality.
Han Wang +4 more
semanticscholar +1 more source
Emerging crowdsensing paradigm enables a large number of sensing applications, where much attention is drawn to the fundamental problems for maximizing the system utility and improving the data quality.
Han Wang +4 more
semanticscholar +1 more source
Multiround Efficient and Secure Truth Discovery in Mobile Crowdsensing Systems
IEEE Internet of Things JournalPrivacy-preserving truth discovery, as a data aggregation algorithm that can extract reliable results from disparate and conflicting data in a privacy-preserving manner, has received a lot of attention in ensuring the reliability and privacy of data in ...
Chenfei Hu +6 more
semanticscholar +1 more source
User Incentivization in Mobile Crowdsensing Systems
2019n this chapter, we present basic design issues of mobile crowdsensing systems (MCS) and investigate some characteristic challenges. We define the basic components of an MCS (the task, the server and the crowd), investigate the functions describing/governing their interactions and identify three qualitatively different types of tasks.
Angelopoulos, Konstantinos Marios +3 more
openaire +2 more sources
Mobile Crowdsensing Ecosystem With Combinatorial Multi-Armed Bandit-Based Dynamic Truth Discovery
IEEE Transactions on Mobile ComputingMobile crowdsensing (MCS) has emerged as a popular and promising paradigm for solving challenging problems by utilizing collective wisdom and resources.
Jia Liu +5 more
semanticscholar +1 more source
IEEE Transactions on Mobile Computing
By utilizing intelligent mobile terminals, mobile crowdsensing (MCS) can realize the sensing data collection effectively and economically. However, the privacy security and freshness quality of the obtained sensing data are two major concerns to be ...
Yaoqi Yang +5 more
semanticscholar +1 more source
By utilizing intelligent mobile terminals, mobile crowdsensing (MCS) can realize the sensing data collection effectively and economically. However, the privacy security and freshness quality of the obtained sensing data are two major concerns to be ...
Yaoqi Yang +5 more
semanticscholar +1 more source
A Preference-Driven Malicious Platform Detection Mechanism for Users in Mobile Crowdsensing
IEEE Transactions on Information Forensics and SecurityExploiting mobile crowdsensing to conduct data collection and analysis brings unprecedented opportunities to promote the development of the Internet of Things(IoT).
Haotian Wang +6 more
semanticscholar +1 more source
Efficient Bilateral Privacy-Preserving Data Collection for Mobile Crowdsensing
IEEE Transactions on Services ComputingMobile crowdsensing (MCS) utilizes ubiquitous mobile devices to collect massive amounts of data and offer various high-quality services. During the data collection and upload process, bilateral access control is implemented to recruit qualified data ...
Axin Wu +4 more
semanticscholar +1 more source
SecDR: Enabling Secure, Efficient, and Accurate Data Recovery for Mobile Crowdsensing
IEEE Transactions on Dependable and Secure ComputingMobile crowdsensing (MCS) has rapidly emerged as a popular paradigm for sensory data collection and benefited various location-based services and applications like road monitoring, smart transportation, and environmental monitoring.
Yifeng Zheng +6 more
semanticscholar +1 more source