At present, the great progress made by the Internet of Things (IoT) has led to the emergence of the Internet of Drones (IoD). IoD is an extension of the IoT, which is used to control and manipulate drones entering the flight area. Now, the fifth-generation mobile communication technology (5G) has been introduced into the IoD; it can transmit ultra-high-definition data, make the drones respond to ground commands faster and provide more secure data transmission in the IoD. However, because the drones communicate on the public channel, they are vulnerable to security attacks; furthermore, drones can be easily captured by attackers. Therefore, to solve the security problem of the IoD, Hussain et al. recently proposed a three-party authentication protocol in an IoD environment. The protocol is applied to the supervision of smart cities and collects real-time data about the smart city through drones. However, we find that the protocol is vulnerable to drone capture attacks, privileged insider attacks and session key disclosure attacks. Based on the security of the above protocol, we designed an improved protocol. Through informal analysis, we proved that the protocol could resist known security attacks. In addition, we used the real-oracle random model and ProVerif tool to prove the security and effectiveness of the protocol. Finally, through comparison, we conclude that the protocol is secure compared with recent protocols.
In recent years, blockchain has received increasing attention and numerous applications have emerged from this technology. A renowned Blockchain application is the cryptocurrency Bitcoin, that has not only been effectively solving the double-spending problem but also it can confirm the legitimacy of transactional records without relying on a centralized system to do so. Therefore, any application using Blockchain technology as the base architecture ensures that the contents of its data are tamper-proof. This paper uses the decentralized Blockchain technology approach to ensure that consumers do not fully rely on the merchants to determine if products are genuine. We describe a decentralized Blockchain system with products anti-counterfeiting, in that way manufacturers can use this system to provide genuine products without having to manage direct-operated stores, which can significantly reduce the cost of product quality assurance. INDEX TERMS Blockchain, ethereum, counterfeit.
Gaussian process regression (GPR) is frequently used for uncertain measurement and prediction of nonstationary time series in the Internet of Things data, nevertheless, the generalization and regression efficacy of GPR are directly impacted by its selection of hyper-parameters. In the study, a non-inertial particle swarm optimization with elite mutation-Gaussian process regression (NIPSO-GPR) is proposed to optimize the hyper-parameters of GRP. NIPSO-GPR can adaptively obtain hyper-parameters of GPR via uniform non-inertial velocity update formula and adaptive elite mutation strategy. When compared with several frequently used algorithms of hyper-parameters optimization on linear and nonlinear time series sample data, experimental results indicate that GPR after hyper-parameters optimized by NIPSO-GPR has better fitting precision and generalization ability.INDEX TERMS Mutation Gaussian process regression, time series regression, hyper-parameters, non-inertial particle swarm optimization.
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