# Blockchain-Assisted Adaptive Reconfiguration Method for Trusted UAV Network
###### Abstract
The UAV network in mission execution faces three major unfavorable objective conditions, which are non-security, complex operation environment, no central support and limited resources of nodes. Therefore, the UAV network not only has to solve the routing reconfiguration brought by topology changes, but also needs to tolerate the internal error nodes generated by the UAV nodes due to their own consumption, being damaged and compromised. Unauthorized access by external nodes must of course also be prevented. The decentralized, de-trusted, and tamper-proof nature of blockchain fits well with the objective nature of mission-based drone networks. In this paper, we propose a stateless permission blockchain system that not only makes the UAV network capable of authentication, but also dynamically isolates untrustworthy nodes by releasing detection scores for all nodes. The continuously updated blockchain provides the UAV network to adaptively perform trusted reorganization of the network while providing a reference for routing. The blockchain-assisted hierarchical Trusted Zone Routing Protocol (BC_TZRP) is essentially a lightweight storage blockchain system based on a zone routing protocol. The system performs data consensus on the local state records of nodes through a two-stage consensus and then implements decision consensus on the data consensus results, and adaptively reconfigures the UAV network based on the decision results. The main contributions of this work are as follows:  
* First, an adaptive configuration method for UAV trusted networks is proposed. The method uses a new block of the blockchain to record the global state assessment of the network nodes at each stage. All UAV nodes reorganize the trusted network based on the updated blockchain and automatically reconfigure the hierarchical logical network based on the newly elected set of delegated authorized nodes to cope with the dynamic nature of the UAV network topology and the time-varying trustworthiness of the network nodes while reducing routing blindness. * Second, a lightweight storage blockchain with a two-stage consensus is designed. Nodes monitor all forwarding behavior of their neighboring nodes at the network layer, and different behaviors are given corresponding trustworthiness discounts. Based on the rhythm of the blockchain consensus, each node submits a state transaction including a local trust assessment of neighboring nodes to the upper network. The blockchain system first performs a data consensus on the transactions of the nodes at each stage and then performs a decision consensus on the data consensus results. The decision consensus result is recorded in the solid new block as trusted network configuration information. The blockchain adds only small decision data to each consensus, while the local state transaction dataset at each stage is discarded directly. * Third, propose a blockchain-assisted hierarchical zone trusted routing protocol. A K-modes clustering method is used to periodically elect the zone centers of the UAV network using a list of neighboring nodes, combined with a global trustworthiness assessment of the nodes as a non-numerical node feature vector. The upper layer network reconstructed by the dynamically updated zone centers manages the UAV network and takes on the main operations in stages, thus balancing the consumption of network resources and minimizing the involvement of erroneous nodes in consensus operations. This not only increases the efficiency of the use of UAV network resources, but more importantly, the fault tolerance of the entire network allows for the presence of more than a third of errant nodes. The rest of the paper is organized as follows. The related work is discussed in Section 2. The system model is in Section 3. A specific description of the recommended scheme (BC_TZRP) in Section 4. In Section 5, We discuss the feasibility of the recommended scheme, including complexity analysis, scalability analysis and security analysis.