Idea
Phishing detection system combining email text and URL analysis to improve security for enterprises and email providers.
Research Paper
Core Innovation
This paper introduces a dual-path detection framework integrating transformer-based NLP with classical machine learning for URL analysis. It uniquely combines semantic and structural features to enhance phishing detection accuracy. The modular design allows flexible deployment as standalone or ensemble systems.
Market Size (TAM)
$20–50B TAM for cybersecurity solutions; $2–10B SAM from enterprise email security and anti-phishing services. Driven by rising phishing threats and regulatory compliance.
Potential Customers & Pain Points
- Enterprises facing sophisticated phishing attacks
- Email service providers needing improved spam filters
- Cybersecurity firms seeking advanced detection tools
Business Model
Subscription-based SaaS platform offering API access and integration with enterprise email security solutions.
Competitive Landscape
- Proofpoint
- Mimecast
- Barracuda Networks
Implementation Challenges
- Integration complexity with existing email systems
- Evolving phishing tactics requiring continuous model updates
- Balancing detection accuracy with computational efficiency
Validation Strategy
- Benchmark against public phishing email and URL datasets
- Pilot deployment with enterprise email providers
- Iterate model based on real-world feedback and threat evolution
Research Paper Overview
Dual-Path Phishing Detection: Integrating Transformer-Based NLP with Structural URL Analysis
Summary
This paper proposes a dual-path phishing detection framework combining transformer-based NLP and classical machine learning to analyze email text and embedded URLs. It uses fine-tuned DistilBERT for semantic analysis and character-level TF-IDF with Random Forest for URL structure analysis. The approach improves detection accuracy and balances performance with computational efficiency. The modular design supports standalone or ensemble deployment, enhancing email security against sophisticated phishing threats.