Endpoint Mapping Framework for Integrated Cybersecurity Response
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Solution Overview
Problem
Existing cybersecurity systems face limitations in integrated incident response capabilities, fragmented visibility, complex procurement protocols for third-party vendors, static defenses against evolving threats, and inadequate infrastructure adaptation, leading to delayed responses and increased vulnerabilities.
Innovation Solution
A customized cybersecurity framework utilizing decentralized compute and data store interface (DCDSI) endpoints, tokenization, and blockchain technology for dynamic threat monitoring, vendor integration, and real-time risk assessment, enhancing data security and interoperability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional cybersecurity systems are used, then basic security functions are provided, but integrated incident response capabilities are limited and visibility is fragmented
Solution Approach 1:
The system segments the cybersecurity architecture into distinct functional modules: DCDSI endpoints for data collection, object packages for standardized data structures, and a processing system for analysis. This modular segmentation enables integrated incident response while maintaining manageable complexity through clear separation of concerns.
Solution Approach 2:
The framework employs universal object packages that can accommodate multiple endpoint types and data formats through standardized schemas. This multi-functionality allows the system to integrate diverse security tools and data sources without requiring custom integration logic for each component, thereby improving reliability while controlling complexity.
2Adaptability or versatility
If static security defenses are implemented, then current threats are addressed, but adaptability to evolving threats is insufficient
Solution Approach 1:
The system implements dynamic security responses through real-time data processing and machine learning models that continuously adapt to emerging threat patterns. The framework dynamically adjusts security measures based on analyzed data from DCDSI endpoints, enabling adaptability to evolving threats while managing complexity through automated decision-making processes.
Solution Approach 2:
The framework incorporates feedback mechanisms where security data from endpoints is continuously collected, analyzed, and used to refine future security responses. This closed-loop feedback system enables the architecture to learn from past incidents and adapt to evolving threats, improving versatility while controlling complexity through systematic learning processes.
3Adaptability or versatility
If multiple third-party vendors are integrated, then comprehensive security coverage is achieved, but procurement protocols become complex
Solution Approach 1:
The system introduces standardized object packages as intermediaries between the security platform and third-party vendors. These object packages act as mediators that translate between different vendor formats and the central processing system, enabling comprehensive vendor integration while simplifying procurement protocols through standardized communication interfaces.
Solution Approach 2:
The framework standardizes vendor integration by transforming diverse vendor-specific parameters into unified data structures through object packages. This parameter standardization enables comprehensive security coverage from multiple vendors while reducing operational complexity by providing a consistent interface for all vendor interactions regardless of their original protocols.
4Productivity
If real-time threat monitoring is implemented, then proactive security responses are enabled, but infrastructure requirements increase
Solution Approach 1:
The system merges multiple security functions into a unified architecture where DCDSI endpoints, object packages, and processing systems work together as an integrated whole. This consolidation enables real-time threat monitoring and proactive responses while reducing infrastructure complexity by eliminating redundant components and streamlining data flow paths.
Data Source
AI summary
Systems, methods, and computer-readable for endpoint integration and mapping are disclosed. A system can include one or more processing circuits configured to identify endpoints and access information. The processing circuits can generate an object package corresponding to the endpoint by initiating the object package based on an identifier corresponding to an endpoint type of which the object package is structured and mapping the access information to an access scheme corresponding to formatted requests to access the endpoints for protection data. The processing circuits can perform an endpoint request by invoking the object package using at least one formatted request and receiving output data with a response to the endpoint request by a DCDSI system. The processing circuits can further update a distributed ledger or data source based on the output data.