Security Intelligence Exchange Using Distributed Ledger Threat Data
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Solution Overview
Problem
Existing cybersecurity systems face challenges such as lack of integrated incident response capabilities, complex procurement processes for incident response services, and inability to dynamically adapt to evolving threats and organizational changes, leading to delayed responses and increased vulnerabilities.
Innovation Solution
A customized cybersecurity framework that utilizes a distributed ledger to collect and analyze incident data, generate entity-specific threat intelligence, and dynamically configure security tools, integrating with vendor marketplaces for immediate response and continuous monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a customized cybersecurity framework with distributed ledger is implemented, then cybersecurity protection effectiveness is improved, but system complexity increases
Solution Approach 1:
The cybersecurity framework is segmented into distinct functional modules: distributed ledger system for threat intelligence storage, entity profile analysis module, security tool configuration module, and automated response module. Each module operates independently but communicates through standardized interfaces, reducing overall system complexity while maintaining protection effectiveness.
Solution Approach 2:
The distributed ledger acts as an intermediary layer between threat intelligence sources and security tools. It standardizes threat data formats and provides a centralized repository that simplifies the interaction between diverse security components, reducing the complexity of integrating multiple security systems.
2Measurement precision
If entity-specific threat intelligence is generated through data analysis, then protection accuracy is improved, but data processing time increases
Solution Approach 1:
Entity profiles and security configurations are pre-analyzed and stored in the distributed ledger before threats occur. When a threat is detected, the system performs a lookup of pre-computed entity-specific intelligence rather than analyzing raw data in real-time, significantly reducing response time while maintaining high accuracy.
Solution Approach 2:
The system changes the parameter of data representation by storing processed, structured entity profiles with pre-extracted security attributes in the distributed ledger. This transformation of raw data into structured intelligence upfront enables rapid querying and application during incident response without real-time processing delays.
3Productivity
If security tools are dynamically configured based on verified intelligences, then response effectiveness is improved, but automation complexity increases
Solution Approach 1:
The system uses standardized configuration parameters and data formats for security tools that can be automatically adjusted based on threat intelligence. By defining a standard set of configurable parameters for common security tools, the system enables automated reconfiguration without requiring complex custom scripts or manual intervention for each tool type.
Solution Approach 2:
The distributed ledger and configuration system are designed with universal interfaces that can work with multiple types of security tools and threat intelligence sources. This multi-functionality allows a single automated configuration mechanism to serve diverse security tools, reducing the need for tool-specific automation logic and simplifying the overall system.
4Difficulty of detecting and measuring
If comprehensive incident data is collected and analyzed, then threat detection capability is improved, but information management complexity increases
Solution Approach 1:
The system extracts only the essential and relevant features from comprehensive incident data for storage in the distributed ledger, such as entity identifiers, threat types, and critical indicators. By filtering and extracting only the most important data elements, the system maintains high threat detection capability while reducing the complexity of managing and processing the full dataset.
Solution Approach 2:
The distributed ledger stores entity-specific threat intelligence in a localized and organized manner, with each entity having its own profile and associated threat data. This local organization of information allows efficient querying and management of relevant data without requiring complex global data structures, simplifying information management while maintaining comprehensive detection capability.
Data Source
AI summary
Systems, methods, and computer-readable storage media for improving cybersecurity protections across entities. One system includes a response system including one or more processing circuits including memory and at least one processor configured to identify or collect incident data corresponding with a cybersecurity incident. The at least one processor further configured to record the incident data in a distributed ledger or data source and analyze the incident data utilizing a cybersecurity model to generate one or more verified intelligences corresponding to at least one cybersecurity threat. The at least one processor further configured to determine the one or more verified intelligences corresponds to at least one of the plurality of entities and decode the one or more verified intelligences into one or more entity-specific data formats. The at least one processor further configured to configure or re-configure at least one security tool.