Game theory in mobile crowdsensing: A comprehensive survey

VS Dasari, B Kantarci, M Pouryazdan, L Foschini… - Sensors, 2020 - mdpi.com
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 …

A comprehensive survey on mobile crowdsensing systems

D Suhag, V Jha - Journal of Systems Architecture, 2023 - Elsevier
Abstract In recent times, Mobile Crowdsensing (MCS) has garnered considerable attention
and emerged as a promising sensing paradigm. The MCS approach leverages the …

Protection of data privacy from vulnerability using two-fish technique with Apriori algorithm in data mining

D Dhinakaran, PMJ Prathap - The Journal of Supercomputing, 2022 - Springer
The confidential data is mainly managed by creating passwords, tokens, and unique
identifiers in an authorized manner. These records must be kept in a safe location away from …

A privacy-preserving aggregation scheme based on negative survey for vehicle fuel consumption data

W Yang, X Chen, Z Xiong, Z Xu, G Liu, X Zhang - Information sciences, 2021 - Elsevier
The vehicle fuel consumption gauge is a vehicle's basic device that usually records the
instantaneous as well as average fuel consumption of the vehicle, which brings a lot of …

CrowdFL: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning

B Zhao, X Liu, WN Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As an emerging sensing data collection paradigm, mobile crowdsensing (MCS) enjoys good
scalability and low deployment cost but raises privacy concerns. In this paper, we propose a …

An AI-enabled three-party game framework for guaranteed data privacy in mobile edge crowdsensing of IoT

J Xiong, M Zhao, MZA Bhuiyan… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The mobile crowdsensing (MCS) technology with a large number of Internet of Things (IoT)
devices provides an economic and efficient solution to participation in coordinated large …

LDP-IDS: Local differential privacy for infinite data streams

X Ren, L Shi, W Yu, S Yang, C Zhao, Z Xu - Proceedings of the 2022 …, 2022 - dl.acm.org
Local differential privacy (LDP) is promising for private streaming data collection and
analysis. However, existing few LDP studies over streams either apply to finite streams only …

An incentive mechanism for privacy-preserving crowdsensing via deep reinforcement learning

Y Liu, H Wang, M Peng, J Guan… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
With the rise of the Internet of Things (IoT), the number of mobile devices with sensing and
computing capabilities increases dramatically, paving the way toward an emerging …

Secure data aggregation of lightweight E-healthcare IoT devices with fair incentives

W Tang, J Ren, K Deng, Y Zhang - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
With rapid development of e-healthcare systems, patients that are equipped with resource-
limited e-healthcare devices (Internet of Things) generate huge amount of health data for …

An efficient hybrid signcryption scheme with conditional privacy-preservation for heterogeneous vehicular communication in VANETs

I Ali, T Lawrence, AA Omala, F Li - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Vehicular ad hoc networks (VANETs) ensure improvement in road safety and traffic
management by allowing the vehicles and infrastructure that are connected to them to …