Web Tag Integrity Protection Against Malicious Pollution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Tagging systems in social networking and web 2.0 platforms are vulnerable to sabotage by malicious agents introducing noise or polluting tags, which can lead to incoherent results and system failures.
Innovation Solution
A system and method that utilizes a dictionary and math library to evaluate the acceptability of proposed tags by calculating their distance from existing tag clusters, rejecting tags that exceed a threshold distance, thereby preventing noise tags from being added to the tag set, without requiring human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If tagging systems allow user-generated tags to be freely added, then the system becomes more adaptable and versatile, but the system becomes vulnerable to malicious sabotage and tag pollution
Solution Approach 1:
The patent applies preliminary action by pre-defining a controlled vocabulary list of acceptable tags before users can add tags. The system evaluates proposed tags against this pre-established list, accepting only tags that match existing entries. This preliminary preparation of the vocabulary list prevents malicious tags from being added while maintaining systematic control over tag quality.
Solution Approach 2:
The patent introduces an intermediary evaluation mechanism that stands between user input and the tag set. This intermediary component automatically assesses proposed tags against the controlled vocabulary list and filtering criteria, acting as a mediator that allows legitimate tags while blocking malicious ones. The intermediary process includes checking tag relevance, uniqueness, and compliance with predefined rules before adding tags to the set.
2Reliability
If manual evaluation of tags is implemented, then tag quality and reliability improve, but system complexity and operational burden increase
Solution Approach 1:
The patent applies self-service by implementing an automated evaluation system that performs tag validation without requiring manual human review. The system independently checks proposed tags against the controlled vocabulary list, evaluates tag relevance using predefined algorithms, and automatically accepts or rejects tags based on objective criteria. This self-service mechanism eliminates the need for complex manual evaluation processes while maintaining high reliability.
Solution Approach 2:
The patent uses parameter changes by transforming the tag evaluation process from subjective manual assessment to objective automated evaluation based on measurable parameters. The system evaluates tags using quantifiable criteria such as match percentage against the controlled vocabulary, tag frequency statistics, and relevance scoring algorithms. This parameter-based approach simplifies the evaluation system while improving consistency and reliability.
3Quantity of substance
If all proposed tags are accepted without filtering, then the tag set becomes more diverse and comprehensive, but noise tags and malicious content pollute the system
Solution Approach 1:
The patent applies taking out by extracting and removing potentially harmful tags from the tag set through automated filtering. The system identifies and extracts noise tags, malicious content, and irrelevant tags using evaluation criteria such as mismatch with the controlled vocabulary, low relevance scores, and suspicious patterns. This extraction process maintains tag diversity by preserving legitimate tags while removing harmful ones.
Solution Approach 2:
The patent converts the potential harm of user-generated content into benefit by using the large volume of user submissions to automatically refine and expand the controlled vocabulary list. Legitimate user tags that pass evaluation are incorporated into the vocabulary list, enhancing its comprehensiveness over time. The system transforms what could be harmful unrestricted input into a beneficial process that continuously improves tag coverage while maintaining quality control.
Data Source
AI summary
The integrity of an existing tag set associated with a web module is protected by reviewing user-generated proposed additions to the tag set to determine whether the proposed addition is appropriate. An initial test is made to determine whether a proposed addition is trivial; e.g., includes strings of the same character. If the proposed addition is not found to be trivial, it is assessed to determine its relatedness to the existing tag set. The proposed addition is made a part of the tag set only if it is found to be sufficiently related to the existing tag set.