Traditional centralized access control has some shortcomings in robustness, trustworthiness and circulation. Blockchains have the advantages of fault tolerance and trust. Smart contracts have the characteristics of automatic execution and flexible expansion. Tokens can well record credential information and transfer easily. In this paper, blockchain, smart contract and token are integrated and applied to access control to solve the shortcomings of traditional access control. First, access control, blockchain, smart contract and token are briefly described. Second, this paper proposes a solution by giving the general data structure of access control token, elaborating the equivalence, split, merge and verification algorithms of access control token, and explaining the system architecture of token-based access control. Last, this paper uses a token-based access control simulation system to verify that token-based access control has certain comparative advantages in robustness, trustworthiness, circulation, concurrency and so on. INDEX TERMS Access control, distributed control, distributed computing, blockchain, smart contract, token.
Blockchain technology gains more and more attention in the past decades and has been applied in many areas. The main bottleneck for the development and application of blockchain is its limited scalability. Blockchain with directed acyclic graph structure (BlockDAG) is proposed in order to alleviate the scalability problem. One of the key technical problems in BlockDAG is the identification of honest blocks which are very important for establishing a stable and invulnerable total order of all the blocks. The stability and security of BlockDAG largely depends on the precision of honest block identification. This paper presents a novel universal framework based on graph theory, called MaxCord, for identifying the honest blocks in BlockDAG. By introducing the concept of discord, the honest block identification is modelled as a generalized maximum independent set problem. Several algorithms are developed, including exact, greedy and iterative filtering algorithms. The extensive comparisons between proposed algorithms and the existing method were conducted on the simulated BlockDAG data to show that the proposed iterative filtering algorithm identifies the honest blocks both efficiently and effectively. The proposed MaxCord framework and algorithms can set the solid foundation for the BlockDAG technology.
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