SPARQL Filter for Linked Data Spam Detection
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Solution Overview
Problem
Linked Data is vulnerable to spam threats due to the lack of effective countermeasures, with conventional binary classifiers failing to detect multi-statement spam threats and existing solutions not addressing the specific challenges of RDF content-based spam in the Web of Data.
Innovation Solution
A method and filter utilizing a SPARQL engine with binary classifiers to screen RDF triples for malicious content, employing SPARQL queries and FILTER functions to identify and quarantine spam triples, ensuring that only non-malicious data is further processed by Linked Data client applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional binary classifiers are used to screen RDF triples, then single-triple spam can be detected, but multi-statement spam threats cannot be detected
Solution Approach 1:
The patent segments the RDF data into individual triples for classification, then uses a separate graph pattern matching stage to detect multi-statement spam threats. This two-stage approach allows the system to handle both single-triple and multi-statement spam effectively by dividing the detection process into manageable parts.
Solution Approach 2:
The patent transitions from analyzing triples in isolation (single dimension) to analyzing graph patterns across multiple triples (multi-dimensional approach). By introducing graph pattern matching as an additional dimension of analysis, the system can detect complex multi-statement spam threats that conventional binary classifiers miss.
2Productivity
If no spam filter is deployed, then all RDF triples are processed by Linked Data clients, but resources are wasted processing malicious content
Solution Approach 1:
The patent implements preliminary filtering of RDF triples before they reach the Linked Data client application. By screening triples in advance using binary classifiers and removing malicious content upfront, the system prevents resource waste while maintaining productive processing of legitimate data.
Solution Approach 2:
The patent extracts and removes malicious RDF triples from the data stream before processing. By taking out spam content through filtering and quarantine mechanisms, the system protects downstream processes from wasting computational resources on malicious data.
3Loss of information
If all RDF triples are processed without filtering, then no data is lost, but user interfaces are polluted with spam content
Solution Approach 1:
The patent introduces a spam filter as an intermediary component between data retrieval and processing. This mediator screens RDF triples, quarantines malicious content, and allows only clean data to reach the Linked Data client, thus preventing UI pollution while preserving legitimate information.
Solution Approach 2:
The patent converts the potential harm of spam content into a benefit by using machine learning classifiers trained on spam characteristics. The harmful spam data becomes training material that improves the filter's ability to detect and remove malicious content, turning a problem into a solution.
Data Source
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AI summary
A method of protecting a computer device running a Linked Data client application from malicious Resource Description Framework - RDF - content in data retrieved by the Linked Data application, by screening RDF triples in data retrieved by the Linked Data client application for malicious RDF content before the RDF triples are further processed by the Linked Data client application, wherein the screening comprises: storing RDF triples from the retrieved data in a cache; employing a SPARQL Protocol and RDF Query Language - SPARQL - engine equipped with a list of SPARQL queries relating to at least one content-based Linked Data spam threat to analyse each of the RDF triples stored in the cache and identify those of the triples which contain RDF content deemed to be malicious; removing from the cache any triples which have been identified as containing malicious RDF content; and allowing triples remaining in the cache to be further processed by the Linked Data client application.