Connected critical autonomous systems (C-CAS) are envisioned to significantly change our life and work styles through emerging vertical applications such as autonomous vehicles and cooperative robots. However, as the scale of the connected nodes continues to grow, their heterogeneity and cybersecurity threats are more eminent, and conventional centralized communications and decision-making methodology are reaching their limit. This paper is the first exploration of a trustworthy and fault-tolerant framework for C-CAS for achieving hyperreliable global decision-making in a trustless environment, where the connected sensors/nodes are less reliable due to either communication failure or local decision error (e.g., by sensing algorithm/AI, etc.). The proposed framework is based on two iconic distributed consensus (DC) mechanisms, practical Byzantine fault tolerance (PBFT) and Raft, under the proposed PICA (Perception-Initiative-Consensus-Action) protocol with wireless connections among the nodes. We first analytically derived consensus reliability in six different system models. The other fundamental performance metrics such as the consensus throughput and latency, node scalability and reliability gain are also analytically derived. These analytical results provide basic design guidelines for wireless Distributed Consensus (WDC) usage in the C-CAS systems. The results show that WDC significantly improves overall system reliability with the increasing number of participating nodes.

In response to the coronavirus pandemic, COVID-19, the use of online media and teaching tools has soared, leading to rampant cheating and plagiarism. To provide a better online environment, A copyright-aware Blockchain-enabled Knowledge Sharing platform named as BeSharing, enables students to share part of their assignments or ideas without the worry of being plagiarized. Thanks to blockchain technology which ensures the safety of encrypted shared files and the immutability of the shared records, the intellectual property rights of students can be protected whenever plagiarism issues occur. At present, we have released the platform with the realization of relevant functions and finished the alpha test. We believe this platform has great potential to foster collaboration among students while protecting their ideas.

The centralized system becomes less efficient, secure, and resilient as the network size and heterogeneity increase due to its inherent single point of failure issues. Distributed consensus mechanisms characterized by decentralization, autonomy, parallelism and fault-tolerance can meet the increasing demands of safety and security in critical interconnected systems. This paper establishes a Node and Link probabilistic failure model in the presence of node and communication link failures for a representative crash fault tolerant distributed consensus protocol: RAFT. The analytical results in terms of the probability density function and the mean value of consensus reliability are derived. Two important reliability performance indicators, Reliability Gain and Tolerance Gain are proposed to indicate the linear relationship between the consensus reliability and two basic parameters, i.e. the joint failure rate and the maximum number of tolerant faulty nodes, which provide the theoretical guidance for quickly deploying a RAFT system. The special case of a distributed consensus network with already a certain number of failures and its adverse impact are evaluated. The Markov probabilistic models, definitions of Reliability Gain and Tolerance Gain, and the analysis methods proposed in this paper can be extended to other consensus mechanisms.

Driven by the development of blockchain infrastructures and the promotion of Web 3, more than 4000 Decentralized Autonomous Organizations (DAOs) have been developed as online organizations jointly owned and managed by their members who work for the same interests. Voting mechanisms as the democratic administration of DAOs without the involvement of central authority, are crucial to both the development of the DAO community and the protection of individual interests. This paper is one of the first analyses of the critical role of voting mechanisms in DAOs' operation. In the absence of systematic studies of voting mechanisms in DAOs, we propose five tiers of decentralization in DAO voting which marks the critical difference between DAO voting and conventional voting. We also define four dimensions to comprehensively evaluate the performance of DAO voting mechanisms, which identify the demands and characteristics of DAO voting and put forward clear design guidelines for voting mechanisms in DAOs. Finally, we take seven typical voting mechanisms as examples and analyze their performance in our proposed evaluation schemes.