Kernel Sensor Detection Strategies for Real-Time Zero-Day Defense
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing computing infrastructure is vulnerable to zero-day attacks and resource-intensive maintenance is needed to keep systems up-to-date, making it difficult to secure against malicious entities.
Innovation Solution
A platform with kernel sensors and analytics components that detect and mitigate zero-day attacks in real-time, using go-micro middleware and embedded analytics to reduce false alarms and scale detection across thousands of nodes without kernel modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If kernel modules are used for detection, then detection capability is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent extracts the detection functionality from the kernel space and places it in user space. Sensors are implemented as user-space processes that communicate with the kernel through standardized interfaces, eliminating the need for complex kernel modules while maintaining detection capabilities.
Solution Approach 2:
The patent introduces sensors as intermediary components between the kernel and analytics platforms. These sensors act as mediators that collect system data through kernel interfaces without requiring direct kernel module integration, simplifying the overall system architecture.
2Reliability
If comprehensive monitoring is implemented, then security detection is improved, but false alarms increase
Solution Approach 1:
The patent implements feedback mechanisms where sensor data is continuously analyzed and refined. Analytics platforms process sensor outputs and provide feedback to adjust detection thresholds and parameters, reducing false alarms while maintaining security detection effectiveness.
Solution Approach 2:
The patent employs dynamic detection strategies where monitoring intensity and thresholds are adjusted based on system state and threat levels. This dynamic approach allows comprehensive monitoring when needed while reducing false alarms during normal operations.
3Speed
If real-time detection is implemented, then response time is improved, but resource consumption increases
Solution Approach 1:
The patent implements periodic sampling and event-driven detection rather than continuous monitoring. Sensors collect data at optimized intervals or trigger on specific events, achieving real-time detection capability while significantly reducing resource consumption compared to continuous monitoring.
Solution Approach 2:
The patent applies partial monitoring strategies where not all system parameters are monitored at maximum intensity simultaneously. Resource allocation is dynamically adjusted to monitor critical parameters in real-time while using lighter monitoring for less critical parameters.
4Area of stationary object
If detection is scaled across multiple nodes, then coverage is improved, but coordination complexity increases
Solution Approach 1:
The patent implements a universal sensor interface and data format that works across different nodes and platforms. This standardized approach allows detection to be scaled across multiple nodes without increasing coordination complexity, as each node operates independently with compatible interfaces.
Data Source
AI summary
Detection strategies for a node are selected and deployed based on the amount of data collection that is associated with various modes of telemetry available to the node.