DACON: A Novel Traffic Prediction and Data-Highway-Assisted Content Delivery Protocol for Intelligent Vehicular Networks

2020 ◽  
Vol 5 (4) ◽  
pp. 501-513 ◽  
Author(s):  
Peng Sun ◽  
Noura Aljeri ◽  
Azzedine Boukerche
2018 ◽  
Vol 73 ◽  
pp. 1-13 ◽  
Author(s):  
Rodolfo I. Meneguette ◽  
Azzedine Boukerche ◽  
Fabrício A. Silva ◽  
Leandro Villas ◽  
Linnyer B. Ruiz ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Sangwon Hyun ◽  
Hyoungshick Kim

Content-Centric Networking (CCN) is considered as a promising alternative to traditional IP-based networking for vehicle-to-everything communication environments. In general, CCN packets must be fragmented and reassembled based on the Maximum Transmission Unit (MTU) size of the content delivery path. It is thus challenging to securely protect fragmented packets against attackers who intentionally inject malicious fragments to disrupt normal services on CCN-based vehicular networks. This paper presents a new secure content fragmentation method that is resistant to Denial-of-Service (DoS) attacks in CCN-based vehicular networks. Our approach guarantees the authenticity of each fragment through the immediate fragment verification at interim nodes on the routing path. Our experiment results demonstrate that the proposed approach provides much stronger security than the existing approach named FIGOA, without imposing a significant overhead in the process. The proposed method achieves a high immediate verification probability of 98.2% on average, which is 52% higher than that of FIGOA, while requiring only 14% more fragments than FIGOA.


Author(s):  
Miguel Baguena ◽  
Carlos T. Calafate ◽  
Juan-Carlos Cano ◽  
Pietro Manzoni

2017 ◽  
Vol 99 ◽  
pp. 93-106 ◽  
Author(s):  
Changqiao Xu ◽  
Wei Quan ◽  
Athanasios V. Vasilakos ◽  
Hongke Zhang ◽  
Gabriel-Miro Muntean

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