Information infrastructure management tools with extractor, secure storage, content analysis and classification and method therefor

What is this patent about?

’301 is related to the field of information management and data processing within distributed computing systems. It specifically addresses the challenges of identifying, classifying, and securing sensitive or high-value information—referred to as select content—that often resides within unstructured or semi-structured data formats across an enterprise network.

The underlying idea behind ’301 is the use of an adaptive filtering framework that transforms raw data into organized, actionable intelligence by separating the essence of a document from its common container. By employing a combination of content-based, contextual, and taxonomic filters, the system creates an aggregated select content repository. This repository does not just store isolated keywords but captures the broader conceptual and relational meaning of the data, allowing the system to learn and refine its ability to handle future information based on previously identified patterns.

The claims of ’301 focus on a method and system for the automated management of data through the activation of categorical filters that trigger specific enterprise-defined actions. The independent claims describe a process where a data input is screened to extract select content and its associated taxonomic or contextual metadata, which is then stored in dedicated data stores. Once this intelligence is aggregated, the system applies a linked data process—such as extraction, archiving, or distribution limiting—to subsequent data inputs based on the results of the initial filtering and the security levels assigned to that content.

In practice, the invention functions as a dynamic gatekeeper that can be triggered manually or automatically by time, system conditions, or specific events like a security breach. When a document or data stream enters the system, it is deconstructed into granular elements. The system then uses its accumulated knowledge to decide whether to copy, extract, or destroy specific parts of the data. This granular data control ensures that sensitive information is physically or logically isolated from the remainder of the document, preventing unauthorized access while maintaining the utility of the non-sensitive portions.

This approach differs from prior solutions that rely heavily on static classification labels or perimeter-based security like firewalls. Traditional systems are often vulnerable if a label is tampered with or a boundary is breached. In contrast, ’301 implements formlessness by dispersing granular data segments across multiple distributed stores. Because the system manages the actual content and its context rather than just the file metadata, it can provide multi-level security where different users see different versions of the same document, reconstructed in real-time according to their specific clearance levels.