Dynamic Rule Modification for Autonomous Security Response
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Solution Overview
Problem
Existing computing systems face challenges in managing and enforcing rules for data access, operations, and security due to time delays, unnoticed quality-of-service reductions, and difficulties in adapting to new devices or security incidents without human intervention.
Innovation Solution
Implementing dynamically modifiable rules that can be applied, enforced, and modified by computing devices without human intervention, using machine-generated actions to detect violations and request rule modifications based on authority levels and consensus among devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human intervention is required for rule modifications, then security and control are improved, but response time and adaptability deteriorate
Solution Approach 1:
The system enables computing devices to autonomously detect data activities, evaluate them against existing rules, and request rule modifications without requiring continuous human intervention. The automated rule modification process allows the system to self-adjust to new security threats and scenarios, resolving the contradiction between maintaining security control and achieving timely response.
2Adaptability or versatility
If rules are made dynamically modifiable without human intervention, then adaptability and response time are improved, but system complexity and control mechanisms worsen
Solution Approach 1:
The system implements a feedback mechanism where computing devices automatically detect data activities, evaluate them against current rules, and request modifications when violations or new scenarios are detected. This closed-loop feedback system enables dynamic adaptation while managing complexity through structured evaluation protocols and authority level hierarchies.
Solution Approach 2:
The rule modification system is segmented into distinct functional components: device-level detection and evaluation, authority-level approval mechanisms, and centralized rule deployment. This segmentation allows complex adaptive behavior to be achieved through coordinated simpler components, reducing overall system complexity while maintaining high adaptability.
3Productivity
If automated rule modification is implemented, then productivity and efficiency are improved, but measurement and detection capabilities worsen
Solution Approach 1:
Computing devices automatically perform detection, evaluation, and rule modification requests without human intervention, significantly improving efficiency. The self-service mechanism maintains detection capability by embedding detection functions within the automated workflow, allowing devices to monitor data activities and trigger appropriate responses autonomously.
Data Source
AI summary
The disclosure generally pertains to the use of a set of dynamically modifiable rules for a computing and communications system. An example method of use involves a first computing device applying a first set of dynamically modifiable rules for operating upon data. The first computing device detects a data activity that violates the first set of dynamically modifiable rules and conveys to a second computing device a request to modify the first set of dynamically modifiable rules. The second computing device may have an authority to autonomously grant permission to modify the first set of dynamically modifiable rules without human intervention. The first computing device may receive from the second computing device, an approval to modify the first set of dynamically modifiable rules, and may start applying a second set of dynamically modifiable rules that is a modified version of the first set of dynamically modifiable rules.