Trusted Node Information Collection Against Sybil Attacks
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Solution Overview
Problem
Existing technologies face difficulties in dealing with Sybil attacks on information such as reviews, making it challenging to collect highly reliable information, and there is a risk of fake information being used as a reference.
Innovation Solution
A decentralized platform framework where nodes share and publish their 'node trust evaluation methods' and 'node information aggregation methods' in a non-tamperable form, allowing users to define and adjust their own evaluation functions based on shared information, and correct them when necessary, to increase reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If decentralized platform technology is used, then service cost and provider responsibility are reduced, but the system becomes vulnerable to Sybil attacks and fake information
Solution Approach 1:
The system performs preliminary trust evaluation by acquiring and storing trust relationships between nodes before information collection. This pre-established trust data allows the system to quickly identify reliable information sources during Sybil attacks without requiring real-time verification, maintaining information reliability while reducing computational overhead and service costs.
Solution Approach 2:
The patent introduces trust relationships as an intermediary mechanism between nodes in the decentralized network. Instead of direct peer-to-peer verification which is costly and complex, the trust relationship acts as a mediator that simplifies the verification process, enabling the system to resist Sybil attacks efficiently with reduced service costs.
2Reliability
If trust relationships are established between nodes, then information reliability improves, but system complexity increases
Solution Approach 1:
The patent segments the complex trust verification process into distinct components: trust relationship establishment, trust data storage, and trust-based information filtering. By dividing the system into these modular functional units, the complexity is managed more effectively while maintaining high information reliability through systematic trust evaluation.
3Area of stationary object
If nodes share evaluation methods and aggregation methods, then the trust range expands and information collection improves, but the risk of tampering increases
Solution Approach 1:
The system implements feedback mechanisms where nodes continuously share and update their evaluation methods and aggregation results. This feedback loop allows the network to adapt to new threats and maintain trust relationships dynamically, expanding the trustworthy information collection range while detecting and resisting tampering attempts through collective verification.
Data Source
AI summary
An information collection apparatus includes: a first acquisition unit configured to specify trusted nodes trusted by a certain node based on a condition, set for each of a plurality of nodes constituting a network, that the node trusts another node, and acquire conditions of each of the trusted nodes; and a second acquisition unit configured to acquire information regarding a certain target from a node specified based on the conditions acquired by the first acquisition unit, thereby increasing a likelihood of collecting highly reliable information.