Endpoint Helper Agent for User-Guided AI Threat Screening
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Solution Overview
Problem
Existing cyber security systems are insufficient in identifying and responding to complex, evolving cyber threats, particularly suspicious hyperlinks, URLs, and emails, due to their inability to effectively combine human intuition with AI-powered analysis.
Innovation Solution
A host-based endpoint agent facilitates bi-directional communication between users and a cyber security system, allowing users to query suspicious links or URLs directly, leveraging AI models for deeper investigation and reducing resource consumption by filtering benign items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional firewalls and endpoint security methods are deployed, then basic protection against certain threats is provided, but the system is insufficient against complex modern threats that change over time
Solution Approach 1:
The system implements dynamic adaptation by continuously learning from new threat data and updating its detection models. The machine learning components are trained on evolving threat patterns, allowing the security system to adapt its behavior and detection capabilities over time rather than relying on static rule sets.
Solution Approach 2:
The system changes its operational parameters by adjusting detection thresholds, analysis depth, and response strategies based on the specific threat being detected. Different threat types trigger different analysis parameters and response mechanisms, allowing the system to optimize its effectiveness for each threat scenario.
2Measurement precision
If AI-powered analysis is conducted on all potential threats, then identification accuracy improves, but resource consumption increases
Solution Approach 1:
The system applies AI-powered analysis selectively rather than universally. It performs full AI analysis only on items that pass initial filtering and show suspicious characteristics, while applying lighter inspection to benign items. This partial application of intensive analysis maintains accuracy for threats while reducing overall resource consumption.
Solution Approach 2:
The system introduces an intermediary filtering layer between initial threat detection and full AI analysis. This intermediate stage pre-screens potential threats using lighter-weight methods, identifying only the most suspicious items for intensive AI analysis, thereby reducing the volume of data requiring computationally expensive processing.
3Reliability
If comprehensive threat analysis is performed on all items, then threat detection completeness improves, but processing time increases
Solution Approach 1:
The analysis process is segmented into multiple stages: initial filtering, intermediate screening, and detailed AI analysis. Each stage processes items at different depths, with only suspicious items advancing to subsequent stages. This segmentation maintains comprehensive detection capability while reducing overall processing time by avoiding exhaustive analysis of all items.
Solution Approach 2:
The system employs periodic analysis with varying intensities rather than continuous full-depth analysis. It performs rapid initial assessments continuously, followed by deeper periodic analysis of suspicious items. This periodic approach with variable intensity maintains detection completeness while optimizing processing time through rhythmically alternating analysis depths.
Data Source
AI summary
Aspects of the invention relate to a cyber security system that may enable an end user to communicate with a cyber security appliance to identify cyber threats across the client system. The system can include one or more host devices each having a user interface and an endpoint agent for facilitating bi-directional communication between the user and a cyber security appliance. The endpoint agent may include a communication facilitation module including a user interaction module configured to communicate with the user interface and a helper module configured to communicate with the cyber security appliance. The endpoint agent is configured to enable the bi-directional communication between the user interface and the cyber security appliance on receiving a query associated with identified unusual behavior.