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Qinglei Kong
Researcher at The Chinese University of Hong Kong
Publications - 33
Citations - 452
Qinglei Kong is an academic researcher from The Chinese University of Hong Kong. The author has contributed to research in topics: Computer science & Paillier cryptosystem. The author has an hindex of 9, co-authored 25 publications receiving 179 citations. Previous affiliations of Qinglei Kong include Nanyang Technological University & Harbin Institute of Technology.
Papers
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FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing
TL;DR: In this paper, the authors review state-of-the-art algorithms in the context of federated learning, namely the deep neural network model and the Gaussian process model, and various distributed model hyper-parameter optimization schemes.
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A privacy-preserving sensory data sharing scheme in Internet of Vehicles
TL;DR: A novel efficient and location privacy-preserving data sharing scheme with collusion resistance with low data querying failure probability is proposed in IoV, which enables the collection and distribution of the data captured by vehicular sensors.
Posted Content
FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing
TL;DR: Experimental results show that near centralized data fitting- and prediction performance can be achieved by a set of collaborative mobile users running distributed algorithms.
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A Privacy-Preserving and Verifiable Querying Scheme in Vehicular Fog Data Dissemination
TL;DR: A secure querying scheme in vehicular fog data dissemination, in which the roadside units act as fog storage devices to cache data at network edge and disseminate data upon querying, can achieve the security goals of unlinkability, confidentiality, and verifiability.
Journal ArticleDOI
Achieving Privacy-Preserving and Verifiable Data Sharing in Vehicular Fog With Blockchain
Qinglei Kong,Le Su,Maode Ma +2 more
TL;DR: This paper presents an efficient, privacy-preserving and verifiable sensory data collection and sharing scheme with a permissioned blockchain in vehicular fog, by combining the homomorphic 2-DNF (Disjunctive Normal Form) cryptosystem and an identity-based signcryption scheme.