4.7 Article

Security-Enhanced Content Caching for the 5G-Based Cognitive Internet of Vehicles

期刊

IEEE NETWORK
卷 35, 期 2, 页码 40-45

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MNET.011.2000407

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资金

  1. National Key Research and Development Program of China [2017YFE0123600]
  2. National Natural Science Foundation of China [61902363, 61802138, 61802139]
  3. Italian MIUR, PRIN 2017 Project Fluidware [CUP H24I17000070001]
  4. Hubei Key Laboratory of Intelligent Geo-Information Processing [KLIGIP-2018B10]
  5. Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS)

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This article discusses the content caching problem in 5G-based cognitive Internet of Vehicles, designs a secure and delay-sensitive content caching scheme, and demonstrates through experiments that it outperforms traditional methods.
With the explosive growth of multimedia contents in vehicular networks and the development of 5G technology come great challenges to the Internet of Vehicles system. By utilizing the storage capability of roadside units, popular contents can be cached in advance during nonpeak periods, which can bring better quality of experience to users. However, it is difficult for the existing content caching schemes in traditional vehicular networks to achieve global control when designing content caching mechanisms. Moreover, some content caching schemes also bring security concerns. Thus, in this article, we first discuss the content caching problem in the 5G-based cognitive Internet of Vehicles. Then we design security enhancement methods with the cognitive engine. Finally, we use a special case to study how to design a secure and delay-sensitive content caching scheme in cognitive vehicular networks. Extensive experiments show that the proposed algorithm outperforms traditional content caching methods.

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