Previous research studies mostly focused on enhancing the security of radio frequency identification (RFID) protocols for various RFID applications that rely on a centralized database. However, blockchain technology is quickly emerging as a novel distributed and decentralized alternative that provides higher data protection, reliability, immutability, transparency, and lower management costs compared with a conventional centralized database. These properties make it extremely suitable for integration in a supply chain management system. In order to successfully fuse RFID and blockchain technologies together, a secure method of communication is required between the RFID tagged goods and the blockchain nodes. Therefore, this paper proposes a robust ultra-lightweight mutual authentication RFID protocol that works together with a decentralized database to create a secure blockchain-enabled supply chain management system. Detailed security analysis is performed to prove that the proposed protocol is secure from key disclosure, replay, manin-the-middle, de-synchronization, and tracking attacks. In addition to that, a formal analysis is conducted using Gong, Needham, and Yahalom logic and automated validation of internet security protocols and applications tool to verify the security of the proposed protocol. The protocol is proven to be efficient with respect to storage, computational, and communication costs. In addition to that, a further step is taken to ensure the robustness of the protocol by analyzing the probability of data collision written to the blockchain. INDEX TERMS Blockchain, distributed ledger technology, radio frequency identification.
Geographic state machine replication (SMR) is a replication method in which replicas of a service are located on multiple continents to improve the fault tolerance of a general service. Nowadays, geographic SMR is easily realized using public cloud services; SMR provides extraordinary resilience against catastrophic disasters. Previous studies have revealed that the geographic distribution of the replicas has a significant influence on the performance of the geographic SMR; however, the optimal way for a system integrator to deploy replicas remains unknown. In this paper, we propose a method to evaluate and rank replica deployments to assist a system integrator in deciding a final replica deployment. In the method, we also propose a novel evaluation function that estimates a latency of SMR protocols with round-trip time (RTT). To demonstrate the effectiveness of the proposed method, we build thousands of geographic SMRs on Amazon Web Services and present experimental results. The results show that the proposed method that estimates a latency based on RTTs can generate consistent rankings with reasonable calculation time.
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