A Privacy‐Preserving Incentive Mechanism for Data Offloading in Satellite‐Terrestrial Crowdsensing

Abstract

Data offloading algorithm is the foundation of urban Internet of Things, which has gained attention for its large size of user engagement, low cost, and wide range of data sources, replacing traditional crowdsensing in areas such as intelligent vehicles, spectrum sensing, and environmental surveillance. In data offloading tasks, users’ location information is usually required for optimal task assignment, while some users in remote areas are unable to access base station signals, making them incapable of performing sensing tasks, and at the same time, there are serious concerns about users’ privacy leakage about their locations. Until today, location protection for task assignment in data offloading has not been well explored. In addition, existing privacy protection algorithms and data offloading task assignment mechanisms cannot provide personalized protection for different users’ privacy protection needs. To this end, we propose an algorithm known as differential private long-term privacy-preserving auction with Lyapunov stochastic theory (DP-LAL) for data offloading based on satellite-terrestrial architecture that minimizes the total payment. This not only gives an approximate optimal total payment in polynomial time but also improves the issue of poor signal in remote areas. Meanwhile, satellite-terrestrial data offloading architecture integrates wireless sensor networks and cloud computing to provide real-time data processing. What is more, we have considered long-term privacy protection goals. We employ reverse combinatorial auction and Lyapunov optimization theorem to jointly optimize queue stability and total payment. More importantly, we use Lyapunov optimization theorem to jointly optimize queue stability and total payment. We prove that our algorithm is of high efficiency in computing and has good performance in various economic attributes. For example, our algorithms are personally rational, budget-balanced, and true to the buyer and seller. We use large-scale simulations to evaluate the proposed algorithm, and compare our algorithm with existing algorithms, our algorithm shows higher efficiency and better economic properties.

Security of Satellite-Terrestrial Communications: Challenges and Potential Solutions

“…Some works are proposed to address the privacy issues that may arise with the satellite-terrestrial crowdsensing. In [49], the authors introduce a satellite-terrestrial architecture with differential privacy for protecting user privacy in real-time data aggregation. The information related to user locations are quantified with differential privacy and the data aggregation is processed with satellite-terrestrial networks for data aggregation with auction-based incentive mechanisms.…”

Security of Satellite-Terrestrial Communications: Challenges and Potential Solutions

“…Satellite-terrestrial crowd sensing is a relatively novel concept that allows real-time data aggregation to assure world wide user participation from all regions of the globe to cover a more sophisticated sensing task [49]. Although it covers a wide range of users, this may also endanger the user privacy by revealing sensitive information related to the user locations.…”

Security of Satellite-Terrestrial Communications: Challenges and Potential Solutions

“…Satellite-terrestrial crowd sensing is a relatively novel concept that allows real-time data aggregation to ensure worldwide user participation from all regions of the globe to cover a more sophisticated sensing task [51]. Although it covers a wide range of users, this may also endanger user privacy by revealing sensitive information related to the user locations.…”

“…Some works are proposed to address privacy issues that may arise with satellite-terrestrial crowdsensing. In [51], the authors introduce a satellite-terrestrial architecture with differential privacy for protecting user privacy in real-time data aggregation. The information related to user locations is quantified with differential privacy and the data aggregation is processed with satellite-terrestrial networks for data aggregation with management mechanisms can help the network to cope with jamming and enable interference-free coexistence, even in very dynamic environments [112].…”