DNS Traffic Prediction Using NXD Variance Analysis
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Solution Overview
Problem
Current methods fail to effectively predict future DNS traffic patterns based on historical Non-Existent Domain (NXD) traffic, which limits the ability to identify potentially valuable domain names and optimize registration strategies.
Innovation Solution
A tool analyzes DNS pre-registration data, including NXD traffic patterns, to calculate the coefficient of variance (CoV) and identify domains as 'original' or 're-registered,' predicting positive domain traffic by evaluating the variance in NXD responses and the size/number of name servers, thereby providing relative monetization values and traffic statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If historical NXD traffic data is analyzed to predict future DNS traffic, then prediction accuracy improves, but the complexity of data processing and analysis increases
Solution Approach 1:
The patent segments the analysis process into distinct components: collecting NXD traffic data from multiple name servers, calculating statistical metrics (mean, variance, standard deviation) for each domain, and generating prediction scores. This segmentation transforms a complex analytical task into manageable, systematic steps that improve prediction accuracy without overwhelming processing complexity
Solution Approach 2:
The patent performs preliminary analysis of NXD traffic patterns before domains are registered, calculating statistical metrics and prediction scores in advance. This preliminary action enables informed domain registration decisions and traffic forecasting before actual DNS traffic occurs, improving prediction accuracy by analyzing pre-registration behavior patterns
2Reliability
If multiple statistical metrics are calculated for each domain, then prediction reliability improves, but the computational time and resources increase
Solution Approach 1:
The patent calculates multiple statistical metrics (mean, variance, standard deviation) for NXD traffic, but applies them selectively to generate a composite prediction score rather than analyzing each metric independently in depth. This partial action approach maintains prediction reliability through multi-metric analysis while avoiding excessive computational time by focusing on key predictive indicators
3Quantity of substance
If DNS pre-registration data is collected from multiple name servers, then data comprehensiveness improves, but the system complexity and data management burden increase
Solution Approach 1:
The patent implements a universal data collection framework that gathers NXD traffic information from multiple name servers using standardized protocols and metrics. This multi-functional approach allows the same analytical system to process data from various sources (different TLDs, registrars, and name servers) without requiring source-specific processing logic, improving data comprehensiveness while managing system complexity through standardization
Data Source
AI summary
Methods and systems analyze historical NXD traffic to predict future DNS traffic. In one embodiment, a system may count NXD responses generated by an Authoritative DNS server during a particular time period and calculate the variance in NXD traffic for domains over time. The system may then generate a coefficient of variance (CoV) value for each domain observed. Finally, the system may predict positive domain traffic based upon the calculated CoV data. In other embodiments, the system may also base the prediction on the classification of domains as “original” domains or “re-registered” domains. In another embodiment, the system may also base the prediction on the “size” of name servers. Additionally, or alternatively, the system may determine the number of unique name servers for a domain and base the prediction on the number of unique name servers for a particular domain name.