Lichen Zhang
Shaanxi Normal University
65 Papers
285 Citations
Lichen Zhang is an academic researcher from Shaanxi Normal University. The author has contributed to research in topics: Computer science & Network packet. The author has an hindex of 13, co-authored 61 publications. Previous affiliations of Lichen Zhang include Chinese Ministry of Education & National Institute of Advanced Industrial Science and Technology.
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Papers
FakeMask: A Novel Privacy Preserving Approach for Smartphones
TL;DR: A deception policy for privacy preservation is applied and a novel technique is presented, FakeMask, in which fake contexts may be released to provably preserve users' privacy, which is a novel privacy checking algorithm and an efficient one to accelerate the privacy checking process.
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Computational models and optimal control strategies for emotion contagion in the human population in emergencies
TL;DR: Novel computational models of emotion contagion are developed and the optimal control strategy with a mixture of vaccination, quarantine and treatment can significantly decrease the scale of the outbreak of negative emotions, and incur the lowest total costs of inhibiting emotion contagions.
52
Spectrum-Availability Based Routing for Cognitive Sensor Networks
TL;DR: This work estimates the spectrum availability and spectrum quality from the view of both the global statistical spectrum usage and the local instant spectrum status, and introduces novel routing metrics to consider the estimation.
43
An on-demand coverage based self-deployment algorithm for big data perception in mobile sensing networks
Yaguang Lin,Yaguang Lin,Xiaoming Wang,Xiaoming Wang,Fei Hao,Fei Hao,Liang Wang,Liang Wang,Lichen Zhang,Lichen Zhang,Zhao Ruonan,Zhao Ruonan +11 more
TL;DR: A novel on-demand coverage based self-deployment algorithm for big data perception based on mobile sensing networks and a new cellular automata model, in which nodes can self-adaptively and intelligently decide the best direction of movement with low energy consumption are proposed.
34
An efficient privacy preserving data aggregation approach for mobile sensing
TL;DR: This work proposes an efficient data aggregation approach by which an untrusted aggregator in mobile sensing can collect the statistics over the data contributed by multiple mobile users, while supporting privacy preservation of each user and data integrity verification.
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