Network Node Voting System for Malicious Peer Detection
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Solution Overview
Problem
Identifying and blacklisting malicious nodes in peer-to-peer networks is challenging due to the lack of central administration and trust issues, making it difficult to prevent the spread of viruses, malware, and denial-of-service attacks.
Innovation Solution
A system that monitors votes from multiple nodes to identify patterns, allowing for the categorization and blacklisting of undesirable nodes based on their behavior, using a method that involves multiple voting sessions and data structure analysis to group nodes with similar or differing opinions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If peer-to-peer networks are used to enable easy data exchange, then accessibility and data sharing capability are improved, but security and trust reliability deteriorate due to lack of central administration
Solution Approach 1:
The patent implements self-service by enabling nodes to autonomously participate in voting processes to categorize and blacklist other nodes. Each node casts votes based on its own observations of network behavior, eliminating the need for a central administrator while maintaining security through distributed decision-making. This resolves the contradiction by preserving data exchange freedom while achieving security through peer-driven surveillance and judgment.
2Measurement precision
If centralized blacklisting systems are used, then identification accuracy is improved, but system complexity and central administration requirements increase
Solution Approach 1:
The patent extracts the blacklisting function from a centralized authority and distributes it across all network nodes. Instead of requiring a complex central administration system, each node independently participates in voting to identify and blacklist malicious nodes. This extraction maintains identification accuracy through collective intelligence while dramatically reducing system complexity by eliminating the need for centralized management infrastructure.
3Speed
If nodes are blacklisted based on single vote, then response speed is improved, but measurement precision and reliability of identification deteriorate
Solution Approach 1:
The patent implements periodic action by conducting multiple voting sessions over time rather than relying on a single vote. Nodes participate in repeated voting cycles that allow for observation of voting patterns and behavior consistency. This periodic approach maintains rapid response capability while improving measurement precision by aggregating evidence across multiple time points, thereby reducing false positives and enhancing the reliability of node identification.
Data Source
AI summary
A system, method and computer program product are provided. In use, votes from a plurality of nodes for node categorization are monitored. Further, a pattern associated with the votes is identified. Thus, malicious nodes may be identified based on the pattern.