Summary of Towards Secure and Efficient Data Scheduling For Vehicular Social Networks, by Youhua Xia et al.
Towards Secure and Efficient Data Scheduling for Vehicular Social Networks
by Youhua Xia, Tiehua Zhang, Jiong Jin, Ying He, Fei Yu
First submitted to arxiv on: 28 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a learning-based algorithm for efficient and secure data transmission scheduling in vehicular social networks, which prioritizes both efficiency and security. The algorithm uses a neural network to enhance data processing capabilities and Q-learning to optimize information exchange while safeguarding privacy through differential privacy during the communication process. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces an innovative scheduling algorithm that tackles the challenges of data transmission in vehicular environments. It combines a neural network for data processing with Q-learning for optimization, ensuring efficient and secure information exchange. This approach outperforms existing state-of-the-art algorithms in vehicular social networks. |
Keywords
* Artificial intelligence * Neural network * Optimization
