Self-Learning Interactive Communications Privileges
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Solution Overview
Problem
Current systems for configuring communications privileges between domains face challenges in managing complex federation rules and maintaining interactive communication integrity, particularly due to spam issues and the need for granular filtering between entities within and outside domains, leading to increased complexity and administrative burdens.
Innovation Solution
Implementing a self-learning system that monitors interactions between entities within and outside a domain to automatically determine and configure interactive communications privileges based on insight information such as capabilities, permissions, associations, and reputation, reducing the need for manual provisioning and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual provisioning and maintenance of federation rules is implemented, then communications privileges can be configured, but administrative complexity and burden increase significantly
Solution Approach 1:
The system enables self-learning of interactive communications privileges by automatically monitoring communications interactions and gathering insight information about outside entities. This automation eliminates the need for manual provisioning and maintenance of federation rules, allowing the system to configure and update communication privileges autonomously based on observed interactions and entity reputations.
Solution Approach 2:
The system continuously monitors communications interactions between inside and outside entities, gathering feedback information about entity behavior, capabilities, and reputations. This feedback loop enables dynamic adjustment of federation rules and communication privileges, allowing the system to adapt to changing conditions without manual intervention.
2Reliability
If granular filtering is implemented for communications from outside domains, then communication integrity is improved, but system complexity increases
Solution Approach 1:
The system applies different filtering and privilege configurations to different outside entities based on their specific characteristics, reputations, and observed behaviors. Instead of uniform filtering rules, the system tailors communication privileges for each outside entity individually, enabling granular control over which entities can initiate communications and what types of interactions are permitted.
Solution Approach 2:
The filtering and privilege configuration is dynamic rather than static. The system continuously learns from communications interactions and automatically adjusts federation rules and communication privileges based on changing entity reputations and interaction patterns, allowing the filtering mechanism to adapt to new threats and legitimate communication needs over time.
3Reliability
If federation rules are constantly provisioned and updated, then communication security is maintained, but rule maintenance becomes difficult and time-consuming
Solution Approach 1:
The system automatically monitors communications interactions, gathers insight information about outside entities, and self-updates federation rules and communication privileges without requiring administrator intervention. This self-maintaining capability ensures continuous security updates while eliminating the time-consuming manual rule maintenance that plagues traditional federation systems.
Solution Approach 2:
The system proactively monitors and learns about outside entities before they become security threats, gathering insight information and establishing baseline communication privileges in advance. By performing preliminary monitoring and analysis, the system is prepared to quickly respond to security concerns without requiring reactive manual rule updates.
Data Source
AI summary
Methods, systems, and computer-readable media for self-learning interactive communications privileges for governing interactive communications with entities outside a domain are disclosed. The interactive communications privileges can be used to process interactive communications requests between entities inside and outside a domain. The requested interactive communications are allowed if the interactive communications privileges configured for the entity outside the domain allow for the requested interactive communications. The interactive communications privileges are determined in an automated, self-learning manner in response to monitoring communication interactions between the entities inside and outside the domain. In this manner, the interactive communications privileges are not required to be provisioned and maintained by an administrator. The interactive communications privileges can be determined by gathering insight about the entities outside the domain. Insight about an entity outside the domain is information that is useful in determining which interactive communications privileges to configure for an entity outside the domain.


