Malicious node isolation method and system, computing power verification terminal and p2p network

Abstract

The invention relates to a method for isolating malicious nodes, comprising: a credit score generation step, initializing the credit score of the neighbor nodes of the current node; a random character string sending step, the current node sends a random character string to the neighbor node; target value acquisition step, the neighbor node searches for the target value according to the random character string, and sends the obtained target value to the current node; the target value verification step, the current node verifies the target value, and updates the target value according to the verified target value The credit score; judging and isolating step, judging the malicious node of the neighbor node through the credit score, and isolating the neighbor node judged as the malicious node. The present invention evaluates the credibility of neighboring nodes by introducing proof of work, and increases the cost of forging a large number of malicious nodes in an unlicensed P2P network to prevent solar eclipse attacks.

Description

technical field [0001] The invention belongs to the technical field of the Internet, and in particular relates to a method and a system for isolating malicious nodes in a P2P network. Background technique [0002] In 1994, Marsh first systematically discussed the formalization of trust. Starting from the concept of trust, he divided the content and degree of trust, and proposed a mathematical model of trust measurement from the subjectivity of trust. Subsequently, scholars such as Adul-Rahman proposed a trust evaluation model based on distributed feedback information for the evaluation of trust in the Internet community. After that, around how to describe the trust of nodes more reasonably and accurately, many scholars put forward many trust management models in various forms for different application modes in the P2P environment from their own perspectives. Summarizing these trust models can be divided into two categories, that is, trust models that rely on third parties ...

AI Technical Summary

Problems solved by technology

However, this method requires at least one central node trusted by each blockchain node to obtain the workload proof data of each blockchain node, and perform operations such as workload threshold calculation, comparison, and isolation, which has actually deviated from the decentralization of the P2P network At the same time, under the premise that the trustworthiness of the central node cannot be guaranteed, there is no guarantee that the real malicious node can be identified

Images