Conditional Action Execution Based on Object Attributes
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Solution Overview
Problem
Traditional methodologies for minimizing time-consuming analyses, such as caching scanned objects and events, are ineffective for write scans and objects that frequently change, leading to reduced overall analysis performance and associated costs.
Innovation Solution
A system and method that conditionally perform actions based on attributes associated with objects, determining trust states to reduce unnecessary processing by selectively performing scans and inspections, thereby optimizing performance and handling write scans effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional caching methodologies are used to minimize time-consuming analyses, then processing time for repeated objects is reduced, but the system becomes ineffective for write scans and frequently changing objects, leading to reduced overall analysis performance
Solution Approach 1:
The patent implements dynamic trust states that can transition between trusted, untrusted, and distrusted states based on object behavior and attributes. This dynamic approach allows the system to adapt to changing object characteristics, particularly for write scans and frequently changing objects, rather than using static caching methodologies that fail to handle such cases effectively.
Solution Approach 2:
The system changes the parameter of object trust evaluation from static caching to dynamic attribute-based assessment. By evaluating multiple attributes (author, application, behavior patterns) and transitioning trust states based on these parameters, the system optimizes analysis performance for both cached and frequently changing objects.
2Speed
If traditional caching methodologies are applied to minimize scans, then processing speed improves for static objects, but the system incurs additional costs and reduced performance for objects that frequently change
Solution Approach 1:
The patent segments the trust evaluation system into distinct components: attribute determination modules, trust state transition logic, and conditional action selection. This segmentation allows the system to handle different object types (static vs. frequently changing) through appropriate trust state transitions without requiring complex monolithic caching logic.
Solution Approach 2:
The trust state acts as an intermediary between object attributes and scan actions. Rather than directly deciding whether to scan based on caching rules, the system uses trust states as a mediator that translates attribute evaluations into appropriate scanning decisions, simplifying the overall system logic.
3Reliability
If comprehensive scans are performed on all objects to ensure security, then detection accuracy improves, but processing time and computational resources increase significantly
Solution Approach 1:
The patent applies partial scanning actions based on trust states. For objects in a trusted state with positive attributes, the system performs reduced or no scanning (partial action). For objects in untrusted or distrusted states, comprehensive scans are performed. This partial action approach maintains detection accuracy for suspicious objects while reducing overall scan time.
Solution Approach 2:
The system implements feedback loops where scan results and object behavior update trust states, which in turn influence future scanning decisions. This feedback mechanism ensures that detection accuracy is maintained through learning from past scan outcomes, while reducing redundant scans on consistently trusted objects.
Data Source
AI summary
A system, method, and computer program product are provided for conditionally performing an action based on an attribute. In use, at least one attribute associated with an object is determined. Additionally, an event associated with the object is identified. Further, at least one action is conditionally performed in association with the event, based on the at least one attribute.