At present, there are few mature solutions to consider security risks in the research field of distributed storage causal consistency.On the basis of hybrid logic clock and HashGraph, combined with trusted cloud alliance technology in trusted cloud platform, a distributed storage causal consistency model (CCT model) with trust constraints was proposed.The CCT model designed identity authentication and consistent data trust verification mechanism on the client side and the server side respectively, and imposed security constraints on the process of data synchronization between data replicas in the cloud storage cluster.Through the simulation experiment, CCT model can identify and verify the identity signature forgery, illegal third party and other security risks in the client and server, and provide the trusted constraint for the system on the premise of causing small performance cost.

Causal consistency is one of the important projects to ensure data consistency in distributed storage.The current research focuses on causal consistency including optimization of clock method,design of the protocol and the optimization of operation transaction sequence.In the actual cloud environment,in addition to clock skew and query amplification,there are also insecure factors such as Trojans and untrusted third parties,which will destroy the causal consistency metadata stored by users,and the consistency of user’s operating results,even affect the availability of the storage environment.From the perspective of performance improvement and security in distributed storage,the clock synchronization,data replications,analysis and design of server protocol,related research progress of the serialization of operational affairs were introduced combined with consensus mechanisms such as blockchain.At the same time,their principlest,advantages,limitations,and different utilities in terms of security constraints were discussed,and then the future development trends and follow-up research directions were point out at last,which would provide a reference and help for the research in this field.

In order to solve the problem of metadata propagation overhead,operation delay and remote update visibility latency in the current causal consistency model,a causal consistency model for distributed data stores based on the shared graph and partial replication strategy was proposed.This model was based on the topology of the shared graph,and each data center stored an arbitrary subset of the data.At the same time,the global stabilization strategy combining shared stable vector and hybrid logical clocks was proposed to provide data consistency guarantees on the premise of ensuring causality.The theoretical analysis and experimental results show that the proposed model can effectively balance the remote update visibility and the metadata overhead compared with the existing models while reducing the operation delay.