Endpoint Baseline Analytics for Integrated Cybersecurity Operations
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Solution Overview
Problem
Current cybersecurity operations are cumbersome and resource-intensive, requiring manual efforts, specialized expertise, and lack integration between disparate systems, leading to inefficiencies and ad hoc processes that hinder real-time status depiction and proactive risk management.
Innovation Solution
A computer-implemented method and system for integrated cybersecurity operations (MSICSO) using a Universal Access Digital Apparatus (UADA) and Unified Application (UA) platform, which integrates data analytics, AI/ML capabilities, and real-time monitoring to provide proactive recommendations and automated responses across multiple cybersecurity systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple independent cybersecurity systems are used to provide specific operational capabilities, then each system can perform its specialized function, but the systems operate in isolation without standard interfaces, creating data silos and requiring manual data extraction and analysis
Solution Approach 1:
The patent implements a universal data lake that serves as a common repository for all cybersecurity systems, enabling standardized data storage and exchange. This data lake provides a universal interface that multiple specialized systems can access, allowing them to maintain their specialized capabilities while sharing data through a common platform, thereby reducing integration complexity and eliminating data silos
Solution Approach 2:
The patent introduces an intermediary layer consisting of the data lake and analytics platform that mediates between independent cybersecurity systems. This intermediary handles data extraction, standardization, and sharing, allowing specialized systems to operate independently while still enabling integrated cybersecurity operations through the mediating platform
2Measurement precision
If manual processes are used for data extraction, analysis, and task execution, then specialized expertise can be applied to complex cybersecurity challenges, but the processes become resource-intensive and time-consuming
Solution Approach 1:
The patent implements automated analytics and machine learning models that perform data analysis and anomaly detection without requiring constant human intervention. The system automatically extracts insights from the data lake, generates security assessments, and provides recommendations, thereby maintaining high analysis accuracy while significantly improving operational efficiency and reducing resource intensity
Solution Approach 2:
The patent performs preliminary data processing, cleaning, and structuring in the data lake before analysis is needed. Analytics models are pre-configured and continuously trained on historical data, so when security events occur, the system can quickly analyze them without requiring manual data preparation, thus maintaining precision while improving productivity
3Adaptability or versatility
If ad hoc workflows are used for cybersecurity operations, then flexibility in responding to unique security challenges is maintained, but quality and integrity issues arise due to lack of standardization
Solution Approach 1:
The patent implements dynamic workflows that combine standardized processes with adaptive elements. The system provides standardized data collection and analysis procedures through the data lake and analytics platform, ensuring consistency and quality, while allowing customized security policies and response procedures to be configured based on specific organizational needs and threat scenarios, thus achieving both reliability and flexibility
Data Source
AI summary
Systems and methods include a computer-implemented cybersecurity data analytics system. An asset inventory is determined that identifies systems in a network. A baseline activity of the systems is determined using the asset inventory. The determining includes monitoring the systems during a time in which cybersecurity is secure. A real-time model of endpoints is generated using the baseline activity. The real-time model of endpoints includes endpoints communicating between systems in the network and reflects the baseline activity of, and communication among, the endpoints during the time in which cybersecurity is secure. The systems are monitored, including detecting, using the real-time model of endpoints, cybersecurity-related anomalies in the network that deviate from the baseline activity. Actionable alerts are generated by the cybersecurity data analytics system by using at least the detected cybersecurity-related anomalies. The actionable alerts are displayed in a user interface and notify of potential and actual process disruptions.