Differential privacy for industrial internet of things: Opportunities, applications, and challenges

B Jiang, J Li, G Yue, H Song - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
The development of Internet of Things (IoT) brings new changes to various fields.
Particularly, industrial IoT (IIoT) is promoting a new round of industrial revolution. With more …

A survey on privacy properties for data publishing of relational data

A Zigomitros, F Casino, A Solanas, C Patsakis - IEEE Access, 2020 - ieeexplore.ieee.org
Recent advances in telecommunications and database systems have allowed the scientific
community to efficiently mine vast amounts of information worldwide and to extract new …

What are the factors affecting the adoption and use of electric scooter sharing systems from the end user's perspective?

M Samadzad, H Nosratzadeh, H Karami, A Karami - Transport policy, 2023 - Elsevier
Since their introduction in 2017, Electric Scooter Sharing systems (ESSs) are shown to
provide numerous benefits for both individuals and society, including convenient green …

Data release for machine learning via correlated differential privacy

H Shen, J Li, G Wu, M Zhang - Information Processing & Management, 2023 - Elsevier
Traditional correlated differential privacy technology usually introduces too much noise,
reducing data availability. Besides, machine learning often confronts training sets of high …

Synthesizing privacy preserving traces: Enhancing plausibility with social networks

P Zhao, H Jiang, J Li, F Zeng, X Zhu… - … /ACM Transactions on …, 2019 - ieeexplore.ieee.org
Due to the popularity of mobile computing and mobile sensing, users' traces can now be
readily collected to enhance applications' performance. However, users' location privacy …

Unraveling behavioral factors influencing the adoption of urban air mobility from the end user's perspective in Tehran–A developing country outlook

H Karami, M Abbasi, M Samadzad, A Karami - Transport Policy, 2024 - Elsevier
The integration of shared, autonomous, electric, and on-demand mobility services
introduces urban air mobility (UAM) as an emerging intra-city transportation service …

[HTML][HTML] MSDP: multi-scheme privacy-preserving deep learning via differential privacy

K Owusu-Agyemeng, Z Qin, H Xiong, Y Liu… - Personal and Ubiquitous …, 2023 - Springer
Human activity recognition (HAR) generates a massive amount of the dataset from the
Internet of Things (IoT) devices, to enable multiple data providers to jointly produce …

Global combination and clustering based differential privacy mixed data publishing

L Chen, L Zeng, Y Mu, L Chen - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the rapid advancement of information technology, a large amount of high-value data
have been generated. To exploit the potential value of Big Data and at the same time to …

Differentially private demand side management for incentivized dynamic pricing in smart grid

MU Hassan, MH Rehmani, JT Du… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In order to efficiently provide demand side management (DSM) in smart grid, carrying out
pricing on the basis of real-time energy usage is considered to be the most vital tool …

Trajectory data collection with local differential privacy

Y Zhang, Q Ye, R Chen, H Hu, Q Han - arXiv preprint arXiv:2307.09339, 2023 - arxiv.org
Trajectory data collection is a common task with many applications in our daily lives.
Analyzing trajectory data enables service providers to enhance their services, which …