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The emergence of vehicular big data has brought a great promotion to better understand characteristics of vehicular networks,grasp needs of users and improve service qualities.However,malicious users and criminals leverage vehicular networks to conduct illegal behaviors,resulting in a decline in the service quality and difficulties in determining the liability in vehicle accidents.At the same time,there are still some security and privacy issues in the vehicular digital forensics,such as the identity privacy of the data provider and the request control of the data requester.Therefore,a secure vehicular digital forensics scheme based on blockchain was proposed.Firstly,a data requester registered with a certificate authority and an anonymous certificate was obtained for the subsequent data uploading.Then,the data user obtained the public-private key pair and user key in registration,which were respectively used for the data requesting and data decryption.Only if certain attributes were held,the right plaintext could be decrypted.Next,a consortium blockchain was jointly established by several institutions with high credibility to record all data transactions.Finally,the security and privacy were experimentally analyzed,and the performance was tested based on the Ethereum platform.

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Based on the movement model similarity evaluation scheme (MMSE), a movement range oriented forwarding and dynamic multi-copies routing protocol (MROFDM) was proposed in vehicular delay-tolerant networks. With the si-milarity among the movement models and the local real-time information of vehicles, this protocol sended packets to the movement scope of destination node. At the same time, copy equilibrium strategy was used to dynamically adjust copy number of different types of packets. MROFDM with some existing multi-copies routing protocols were compare in simulation. The simulation results verify the performance advantage of MROFDM, and show the adaptability of MROFDM with different proportions of movement models.

A vehicle position estimation algorithm base on least square optimization was prposed.Firstly,the algorithm deduced the convex constraint condition which the distance matrix had to conform within a short time interval.Then,the least square method was employed to estimate the vehicles’ relative position.Finally,the local maps were merged into the global map.Simulation results demonstrate that the algorithm can achieve preferable estimation accuracy,and meet the real time constraint in vehicular networks.

The implementation complexity of the traditional relay selection strategies is too high to be affordable. To solve this problem, this paper proposed a novel relay selection scheme based on partial channel state information (CSI) and non-orthogonal signaling. In this scheme, only the CSI regarding the source-relay links was exploited to select the best relay. Besides that, it introduced the non-orthogonal design to harvest the diversity gain and improved the error performance. Numerical results demonstrate that, compared to the traditional candidates, the proposed method can lower the system outage probability and the bit error probability by an order in medium to high signal-to-noise (SNR) regions. [ABSTRACT FROM AUTHOR]

This paper investigated the problem of warning message dissemination in vehicular networks, and proposed a protocol called WMD for efficient warning message dissemination. In WMD, time was divided into frames with several time slots in length. Each time slot was further divided into two subslots. It used the first subslot for acquiring neighbor position in real time, and the second subslot for disseminating warning message. In order to acquire neighbor position in real time, WMD adopted an adaptive message transmission strategy. Based on an analytical framework, this paper theoretically determined the optimal configurations for number of probe messages and frame length. Based on real traces of vehicles, this paper conducted real trace-driven simulations. Performance results demonstrate that WMD can achieve faster dissemination speed and higher receiving ratio compared with some other alternative protocols. [ABSTRACT FROM AUTHOR]

Some previous works had proposed some replication-based routing protocols, such as epidemic routing, but they couldn't achieve high deliver ratio at a low deliver cost. This paper designed an adaptive replication-based routing protocol called ARR for efficient routing in vehicular networks. ARR was a fully distributed protocol. The goal of ARR was twofold, first, ARR delivered the majority of the messages generated in time-to-live; second, ARR introduced as little deliver cost as possible. To achieve high deliver ratio at a low deliver cost, ARR adopted an adaptive strategy for the number of copies of a message. In addition, this paper proposed two methods for distributing message copies. Based on real traces of vehicles, this paper conducted real trace-driven simulations. Performance results demonstrate that ARR can achieve significantly high deliver ratio at a low delivery cost compared with the other four alternative protocols. [ABSTRACT FROM AUTHOR]