Enhancing Monitoring Performance: A Microservices Approach to Monitoring with Spyware Techniques and Prediction...

Area of Science:

• Computer Science
• Cybersecurity
• Software Engineering

Background:

• Organizations face significant risks from sensitive data leaks and hate speech, leading to financial, reputational, and psychological damage.
• Effective monitoring of computer usage is crucial for mitigating these threats and ensuring a secure digital environment.

Purpose of the Study:

• To present a comprehensive microservices-based solution for monitoring organizational computer usage.
• To compare the performance of Spring Boot and Quarkus for implementing such a system.
• To evaluate the system's effectiveness in detecting data leaks, suspicious behaviors, and hate speech.

Main Methods:

• Development of a microservices architecture incorporating spyware techniques for data capture.
• Implementation of a web application for alert management and predictive modeling for threat detection.
• Comparative performance analysis using objective metrics and benchmarks for Spring Boot and Quarkus.

Main Results:

• Quarkus demonstrated substantial performance improvements over Spring Boot.
• Memory usage reduced by up to 80%, CPU usage by 95%, and system uptime decreased by 119% with Quarkus.
• The system effectively detects data leaks, suspicious behaviors, and hate speech.

Conclusions:

• The proposed microservices solution provides a robust framework for enhancing organizational security.
• Quarkus offers significant performance advantages over Spring Boot for developing such security monitoring systems.
• The findings guide developers and architects in making informed technology choices for enhanced security.