Fog computing for next-generation internet of things: fundamental, state-of-the-art and research challenges

A Hazra, P Rana, M Adhikari, T Amgoth - Computer Science Review, 2023‏ - Elsevier
In recent times, the Internet of Things (IoT) applications, including smart transportation, smart
healthcare, smart grid, smart city, etc. generate a large volume of real-time data for decision …

[HTML][HTML] Integration of blockchain technology and federated learning in vehicular (iot) networks: A comprehensive survey

AR Javed, MA Hassan, F Shahzad, W Ahmed, S Singh… - Sensors, 2022‏ - mdpi.com
The Internet of Things (IoT) revitalizes the world with tremendous capabilities and potential
to be utilized in vehicular networks. The Smart Transport Infrastructure (STI) era depends …

Privacy and robustness in federated learning: Attacks and defenses

L Lyu, H Yu, X Ma, C Chen, L Sun… - IEEE transactions on …, 2022‏ - ieeexplore.ieee.org
As data are increasingly being stored in different silos and societies becoming more aware
of data privacy issues, the traditional centralized training of artificial intelligence (AI) models …

Decentralized privacy using blockchain-enabled federated learning in fog computing

Y Qu, L Gao, TH Luan, Y **ang, S Yu… - IEEE Internet of …, 2020‏ - ieeexplore.ieee.org
As the extension of cloud computing and a foundation of IoT, fog computing is experiencing
fast prosperity because of its potential to mitigate some troublesome issues, such as network …

Differential privacy techniques for cyber physical systems: A survey

MU Hassan, MH Rehmani… - … Communications Surveys & …, 2019‏ - ieeexplore.ieee.org
Modern cyber physical systems (CPSs) has widely being used in our daily lives because of
development of information and communication technologies (ICT). With the provision of …

Edge computing: A survey

WZ Khan, E Ahmed, S Hakak, I Yaqoob… - Future Generation …, 2019‏ - Elsevier
In recent years, the Edge computing paradigm has gained considerable popularity in
academic and industrial circles. It serves as a key enabler for many future technologies like …

Deep learning in smart grid technology: A review of recent advancements and future prospects

M Massaoudi, H Abu-Rub, SS Refaat, I Chihi… - IEEE …, 2021‏ - ieeexplore.ieee.org
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …

Blockchain-based anonymous authentication with key management for smart grid edge computing infrastructure

J Wang, L Wu, KKR Choo, D He - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Achieving low latency and providing real-time services are two of several key challenges in
conventional cloud-based smart grid systems, and hence, there has been an increasing …

Local differential privacy and its applications: A comprehensive survey

M Yang, T Guo, T Zhu, I Tjuawinata, J Zhao… - Computer Standards & …, 2024‏ - Elsevier
With the rapid development of low-cost consumer electronics and pervasive adoption of next
generation wireless communication technologies, a tremendous amount of data has been …

Towards fair and privacy-preserving federated deep models

L Lyu, J Yu, K Nandakumar, Y Li, X Ma… - … on Parallel and …, 2020‏ - ieeexplore.ieee.org
The current standalone deep learning framework tends to result in overfitting and low utility.
This problem can be addressed by either a centralized framework that deploys a central …