Context-Aware SASE Engine for Dynamic Security Profiles
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Solution Overview
Problem
The existing security access service edge (SASE) framework provides a single security approach that is not optimal for specific endpoints, applications, or tenants, lacking the flexibility to adapt dynamically to changing security needs and behaviors.
Innovation Solution
A context-aware SASE engine is deployed on network edge devices to generate security profiles based on endpoint information and default profiles from enterprise networks, enabling dynamic and autonomous security adjustments tailored to specific endpoints, applications, and tenants, with feedback loops for continuous updates and vulnerability management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single security approach is used for all users in the SASE framework, then the system is simple to manage and implement, but it cannot provide optimal security capabilities tailored to specific endpoints, applications, or tenants
Solution Approach 1:
The patent segments the unified security approach into multiple tenant-specific security profiles, each tailored to specific endpoints, applications, or tenants. The SASE framework divides security capabilities into discrete, configurable units that can be independently customized and applied to different segments of the network, allowing optimal security for each segment without requiring complete system redesign.
Solution Approach 2:
The patent implements dynamic security profiles that can be automatically adjusted based on contextual information such as endpoint behavior, application performance metrics, and security threats. The system dynamically modifies security parameters in real-time without requiring manual reconfiguration, enabling adaptability while maintaining manageable complexity through automated decision-making processes.
2Reliability
If context-aware security profiles are generated for each endpoint, then optimal security capabilities are provided, but the processing time and computational resources increase
Solution Approach 1:
The patent pre-generates and caches security profiles based on endpoint characteristics, application types, and tenant requirements before actual security evaluation is needed. By preparing security configurations in advance and storing them for quick retrieval, the system reduces real-time processing requirements while maintaining high reliability in security assessments.
Solution Approach 2:
The patent implements feedback mechanisms that use historical security evaluation data to continuously refine and optimize security profiles. The system learns from past security events, endpoint behaviors, and threat patterns, automatically adjusting profiles to improve accuracy while reducing the computational overhead required for generation and evaluation over time.
Data Source
AI summary
Techniques for a context-aware secure access service edge (SASE) engine for generating security profile(s) associated with endpoint device(s) accessing the network and using the security profile(s) to evaluate a traffic flow from the endpoint device(s). The SASE engine may execute on an edge device of a computing resource network and may be configured to maintain a security profile database including an endpoint security profile mapping. Endpoint device(s) accessing the network may share endpoint, application, and/or user specific information with the SASE engine so that the SASE engine may generate a security profile specific to the endpoint, application, and/or user. Additionally, an enterprise network, associated with endpoint device(s) accessing the network, may provide default SASE security profile templates to the SASE engine. Further, a feedback loop may be established between the SASE engine and the endpoint device(s), enabling the SASE engine with the ability to autonomously and dynamically update security profiles.