Cybersecurity Log Integration for Adaptive Threat Response
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Solution Overview
Problem
Existing cybersecurity measures are inadequate in addressing the constantly evolving and sophisticated cybersecurity threats, as they are often thwarted by cybercriminals adapting their techniques shortly after detection tools are developed, necessitating constant vigilance and adaptation.
Innovation Solution
An integrated cybersecurity threat management system that ingests, sorts, and evaluates heterogeneous log files from multiple network-connected threat protection applications to identify and respond to threats, utilizing machine learning and human expertise to generate adaptive responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple separate cybersecurity applications are used to detect threats, then detection coverage is improved, but system complexity and difficulty of managing heterogeneous data increases
Solution Approach 1:
The patent combines multiple separate cybersecurity applications into a single integrated platform that ingests log files from various sources (firewall, antivirus, intrusion detection, etc.). The system merges data from heterogeneous sources into a unified analysis engine, reducing the complexity of managing multiple separate tools while maintaining comprehensive detection coverage.
Solution Approach 2:
The integrated cybersecurity platform performs multiple functions within a single system: it ingests logs from various sources, analyzes threats using machine learning, generates reports, and provides response mechanisms. This multi-functional approach eliminates the need for separate specialized tools while maintaining broad detection capabilities.
2Measurement precision
If heterogeneous log files from multiple sources are analyzed, then threat detection accuracy is improved, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary sorting and categorization of log files as they are ingested, organizing data by source, type, and relevance before detailed analysis. This preliminary processing reduces the computational burden during threat detection by pre-structuring the heterogeneous data, thereby maintaining accuracy while reducing processing time.
Solution Approach 2:
The system creates standardized copies of heterogeneous log data in a unified format suitable for analysis. By transforming diverse log structures into a common schema during the ingestion phase, the system enables efficient processing without losing the precision needed for accurate threat detection.
3Adaptability or versatility
If machine learning algorithms are used to evaluate threat data, then response adaptability is improved, but computational complexity and resource requirements increase
Solution Approach 1:
The machine learning algorithms continuously learn and adapt from the ingested threat data, automatically improving their detection capabilities without requiring manual reconfiguration. The system serves itself by using its own operational data to refine its models, enabling adaptive responses while managing computational complexity through incremental learning rather than complete retraining.
4Speed
If real-time threat analysis is performed on all log data, then response speed is improved, but system resource consumption increases
Solution Approach 1:
The system applies different levels of analysis to different portions of log data based on their relevance and risk level. High-priority logs from critical systems undergo immediate real-time analysis, while lower-priority logs are processed with less intensive methods or batched for later analysis. This localized quality approach maintains fast response times for critical threats while reducing overall resource consumption.
Data Source
AI summary
Disclosed techniques include integrated cybersecurity threat management. A plurality of network-connected cybersecurity threat protection applications is accessed. A plurality of heterogeneous log files is ingested, wherein the log files are generated by at least two of the cybersecurity threat protection applications. The plurality of heterogeneous log files that were ingested is evaluated to enable identification of cybersecurity threat protection application capabilities. Each of the plurality of log files is sorted. The sorting enables identification of cybersecurity threat protection elements among the plurality of log files. The cybersecurity threat protection elements that were identified are integrated. The integrated cybersecurity threat protection elements are evaluated. At least one response for cybersecurity threat management is generated, based on a result of the evaluating. The response is provided to a cybersecurity threat management entity. The cybersecurity threat management entity is a security orchestration automation and response application.