Trigger-Based Harvesting for Malignant Content Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Efficiently detecting and tracking malignant content in networked environments, such as the Internet, is challenging due to its fluid nature and the difficulty in searching across multiple data channels, leading to resource-intensive processes that strain server performance and time efficiency.
Innovation Solution
A system and method that perform multi-step content searching, using a coarse search to identify suspicious content, followed by targeted micro-harvests to focus on specific areas, reducing the need for generic searches across entire networks, thereby improving server performance and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If generic search terms are used to search the entire networked environment, then malignant content can be detected, but computing resources and time are excessively consumed
Solution Approach 1:
The patent segments the search process into two distinct phases: coarse harvesting that searches broad areas with generic terms, and fine harvesting that targets specific suspicious content with refined terms. This segmentation allows the system to maintain detection capability while reducing overall resource consumption by limiting intensive searching to only suspicious areas rather than the entire networked environment.
Solution Approach 2:
The patent applies partial action by performing comprehensive generic searches only in coarse harvesting phases, then switching to targeted fine harvesting for suspicious content. This avoids the excessive resource consumption of continuously performing full-scale generic searches across the entire networked environment, while still maintaining reliable detection through periodic coarse searches.
2Reliability
If generic search terms are used to search the entire networked environment, then malignant content can be detected, but server performance deteriorates
Solution Approach 1:
The patent divides the harvesting operation into coarse and fine phases, where coarse harvesting uses generic terms for broad coverage and fine harvesting uses specific terms for targeted searching. This segmentation prevents server performance deterioration by avoiding continuous full-scale generic searches, while maintaining detection reliability through the two-phase approach.
Solution Approach 2:
The system performs periodic coarse harvesting with generic search terms to identify suspicious content, then switches to fine harvesting with specific terms. This periodic alternation between broad and targeted searching maintains detection capability while allowing server performance to recover between intensive search phases.
3Measurement precision
If coarse search is performed across the entire networked environment, then suspicious content can be identified, but time consumption increases
Solution Approach 1:
The patent segments the search process into coarse harvesting for broad suspicious content identification and fine harvesting for targeted verification. This segmentation reduces total search time by limiting comprehensive searching to periodic coarse phases, while using faster targeted fine harvesting for suspicious areas.
Solution Approach 2:
The patent performs preliminary coarse harvesting to identify suspicious content and uniform resource locators before conducting fine harvesting. This preliminary action allows the system to focus subsequent searching on specific suspicious areas rather than repeatedly searching the entire networked environment, significantly reducing total time consumption.
4Productivity
If multi-step searching with micro-harvests is implemented, then resource efficiency improves, but system complexity increases
Solution Approach 1:
The patent implements segmentation by dividing the harvesting system into coarse harvesting and fine harvesting components with distinct functions. While this segmentation improves resource efficiency by targeting searches, it does increase system complexity by requiring coordination between multiple harvesting engines and state management.
Solution Approach 2:
The system uses feedback mechanisms where fine harvesting results feed back into the coarse harvesting process, allowing the system to learn from previous searches and refine future search strategies. This feedback loop improves resource efficiency over time but adds complexity to the system architecture and state management.
Data Source
AI summary
Exemplary embodiments of the present disclosure relate to systems, methods, and non-transitory computer-readable media for searching content in a networked environment to identify malignant content and ultimately for removing the malignant content from the networked environment. Content hosted by one or more servers in a networked environment can initially be searched based on one or more search terms, and attributes from each result in a first set of results returned in response to searching the content hosted by the one or more servers can be extracted. Each result can be tagged based on the attributes, and at least one supplement search of the content hosted by the one or more servers in the networked environment can be triggered in response to at least one of the results being tagged as malignant content.