Combo-squatting Domain Linkage via Nameserver Grouping

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Solution Overview

Problem

Current computer networking systems are ineffective in detecting malicious domains, known as ComboSquatting domains, which can impersonate legitimate companies or services by incorporating trademarked names, making it difficult to identify and mitigate potential malicious activities such as phishing or malware.

Innovation Solution

A method and system that groups domain names by nameservers, splits words in each domain name, generates a wordlist, finds feature words, and extracts malicious domain names and corresponding registrant data, using techniques like inverse document frequency to identify potentially malicious domains registered by the same entity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If domain names are grouped by nameserver and analyzed using word splitting and feature extraction, then the ability to identify malicious domains is improved, but the system complexity increases

Engineering Contradiction:
Improvedetection accuracyVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments domain names into individual words using word splitting, creating wordlists from domain names. This segmentation allows for easier analysis of individual components (words) rather than treating entire domain names as single units, improving detection accuracy while managing complexity through modular processing

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces feature words as intermediary elements that connect domain names to their malicious intent. By extracting and analyzing feature words (such as uncommon or suspicious terms) from domain names, the system creates an intermediate layer of analysis that improves detection without requiring direct complex analysis of all domain name components

Inventive Principle:
Principle #24Intermediary (Mediator)

2Reliability

If comprehensive domain analysis is performed to identify malicious domains, then detection capability is improved, but the time required for analysis increases

Engineering Contradiction:
Improvedetection capabilityVSAvoidanalysis time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent performs preliminary word splitting and wordlist generation from domain names before the actual malicious domain detection process. By pre-processing domain names into wordlists and identifying feature words in advance, the system reduces the computational burden during the detection phase, improving reliability while minimizing analysis time

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent extracts only the essential feature words from domain names rather than analyzing entire domain names in full detail. By taking out and focusing on specific suspicious or uncommon words that indicate malicious intent, the system achieves reliable detection with reduced analysis time compared to comprehensive domain name analysis

Inventive Principle:
Principle #2Taking out (Extraction)

Data Source

PatentUS11178175B2Combo-squatting domain linkage
Publication Date: 2021.11.16 INTERNATIONAL BUSINESS MACHINE CORPORATION
  • US11178175B2 patent drawing
  • US11178175B2 patent drawing
  • US11178175B2 patent drawing

AI summary

A computer-implemented method for linking combo-squatting domains is provided. The method includes grouping domain names into nameserver groups based on a nameserver for each of the domains. Each of the domain names contain valued words. The method also includes splitting words in each domain name and generating a wordlist for each of the nameserver groups. The method further includes finding feature words among the nameserver groups, and extracting malicious domain names which contain the feature words in each of the nameserver groups. The method further includes outputting, for each of the nameserver groups, the malicious domain names and corresponding registrant identifying data based on the feature words.