Blockchain-Based Trust Model for Inter-Domain Routing
Source abstract
Abstract
Border Gateway Protocol (BGP), as the standard inter-domain routing protocol, is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems (AS). BGP nodes, communicating in a distributed dynamic environment, face several security challenges, with trust being one of the most important issues in inter-domain routing. Existing research, which performs trust evaluation when exchanging routing information to suppress malicious routing behavior, cannot meet the scalability requirements of BGP nodes. In this paper, we propose a blockchain-based trust model for inter-domain routing. Our model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the blockchain. The BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective alliance. We incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing service. We forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing behavior. We use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust model. Compared with the classical trust model, our trust model not only saves more storage overhead, but also provides higher security, especially reducing the impact of collusion attacks.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Blockchain Technology Applications and Security · Cloud Data Security Solutions · Software-Defined Networks and 5G
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (26)
Show source-provided references
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