UTDRS - Unified Threat Detection & Response System

AI-driven platform for real-time threat detection and automated response in enterprise environments.

Python

TensorFlow

Kubernetes

Elasticsearch

Kafka

FastAPI

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Problem Statement

Organizations struggle with overwhelming security alerts and slow response times to cyber threats, leading to data breaches and financial losses.

Solution Approach

Built an intelligent system that uses machine learning to analyze security logs, correlate threats, and automate response actions while providing human oversight.

System Architecture

Microservices architecture with event-driven processing, distributed ML inference, and secure API gateways for enterprise integration.

Technical Challenges & Solutions

Key Challenges

Processing high-volume security logs in real-time
Reducing false positives while maintaining threat detection accuracy
Ensuring system reliability in enterprise environments
Implementing ethical AI decision-making frameworks

Outcomes Achieved

97% accuracy in threat detection
60% reduction in mean time to respond (MTTR)
Top 5 finalist in Mozilla Responsible Computing Challenge 2025

Performance Metrics

97%

Detection Accuracy

60%

MTTR Reduction

< 2%

False Positive Rate

Lessons Learned

The importance of explainable AI in security systems
Building trust through transparency in automated decision-making
The value of human-AI collaboration in high-stakes environments

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