Browser Activity Monitoring for Cloud Data Exfiltration Detection

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Solution Overview

Problem

Existing systems lack effective methods to detect data exfiltration, particularly in cloud environments, where insider threats and unauthorized data transfers are difficult to identify and mitigate.

Innovation Solution

Implementing a data platform with agents that monitor compute assets for various activities, creating polygraphs of user behavior and network interactions, and using data analytics to detect anomalies and deviations from typical patterns, enabling real-time detection and response to potential data exfiltration.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If agents continuously monitor compute assets and collect detailed data, then detection capability is improved, but data volume and system complexity increase

Engineering Contradiction:
Improvedetection capabilityVSAvoiddata volume
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent extracts only the necessary data elements from continuous monitoring streams by collecting specific attributes (user identity, source/destination IPs, ports, protocols, byte counts, timestamps) rather than all possible data. The polygraph structure further extracts and represents only the essential relationships and patterns needed for anomaly detection, filtering out redundant information while maintaining detection capability.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The monitoring system is segmented into distributed agents deployed on individual compute assets, each handling local data collection independently. The central data platform segments processing into multiple components: data ingestion, polygraph construction, anomaly detection, and alerting. This segmentation allows scalable data handling and reduces the complexity burden on any single component.

Inventive Principle:
Principle #1Segmentation

2Reliability

If comprehensive monitoring of user behavior and network interactions is implemented, then data exfiltration detection is improved, but system complexity increases

Engineering Contradiction:
Improvesecurity monitoring effectivenessVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The polygraph data structure serves multiple functions simultaneously: it represents normal behavior baselines, enables anomaly detection, supports threat hunting, and provides forensic analysis capabilities. The same collected data is used for both immediate detection and long-term security posture assessment, reducing the need for separate specialized systems.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces a polygraph as an intermediary representation layer between raw monitoring data and security analysis. This polygraph structure simplifies complex network behavior into manageable graphs of entities and relationships, making the system more manageable and the detection algorithms more efficient without sacrificing monitoring comprehensiveness.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Speed

If real-time detection is achieved through continuous monitoring, then response time is improved, but computational resources are consumed

Engineering Contradiction:
Improvedetection speedVSAvoidcomputational resources
Core Design Contradiction:
SpeedVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary actions by continuously updating the polygraph with baseline behavior patterns and pre-processing data into structured representations. This preparation enables faster anomaly detection during actual threats, as the system only needs to compare current activity against pre-established polygraph models rather than analyzing raw data in real-time.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The anomaly detection process uses partial action by focusing computational resources only on detecting deviations from normal behavior rather than analyzing all data uniformly. The polygraph enables the system to ignore normal patterns and concentrate computation only on identifying anomalies, reducing overall computational burden while maintaining real-time detection capability.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentUS12598205B1Browser-based detection of data exfiltration
Publication Date: 2026.04.07 FORTINET INC
  • US12598205B1 patent drawing
  • US12598205B1 patent drawing
  • US12598205B1 patent drawing

AI summary

Browser-based detection of data exfiltration includes gathering first information describing browser activity of a browser of a device and generated by a browser extension on the device; and determining whether the first information indicates a data exfiltration. The first information may include data input to the browser and the determination of whether the first information indicates a data exfiltration is based on the data input.