Turing Machine-Based Cross-Network Isolation and Data Exchange Theory Model

Abstract

Due to the confidentiality of the classified information system, it is isolated from the external network, but it is necessary to exchange data with an external network. This makes data exchange security between classified networks an important problem. Previous research focused on using access control policies to limit data access at different security levels, using some security checks to detect the security of the data itself. The security threat of the access control policy itself will threaten the data exchange between the classified networks. Moreover, the data should be performed security check isolated from user during the physical transmission to prevent the attack behavior which bypass the data security check from the user side. At present, the cross-network isolation and data exchange models are designed based on fixed business scenarios and lack generality. Therefore, this paper proposes a Turing machine-based theoretical model for cross-network isolated data exchange. This model consists of two parts: the proof system module and the physical transmission channel module. The proof system module uses an interactive Turing machine to model the part of the operational security and data security check of the communicating party’s authority to provide security and versatility. The physical transmission channel module isolates different networks and provides a detection mechanism independent of the communication parties to ensure the security and efficiency of the transmission. The proof given shows that the theoretical model can exchange data efficiently and safely. Finally, based on the given theoretical model, an intuitive cross-network isolation and data exchange function model is constructed in the form of a functional tree to illustrate the model versatility.