Automated Phishing Detection with AI Powered Email Security

Automated Phishing Detection and Email Security

1. Workflow Overview

This workflow outlines the process for implementing automated phishing detection and email security utilizing AI research tools in the cybersecurity domain.

2. Stakeholders

• Cybersecurity Analysts
• IT Support Teams
• End Users
• AI Developers

3. Workflow Steps

Step 1: Data Collection

Gather email data from various sources including:

• Email servers
• User reports
• Threat intelligence feeds

Step 2: Data Preprocessing

Utilize Natural Language Processing (NLP) tools to clean and prepare the data.

• Remove duplicates
• Normalize text formats
• Extract relevant features

Step 3: AI Model Development

Develop machine learning models to identify phishing attempts.

• Utilize supervised learning algorithms such as:
• Random Forest
• Support Vector Machines (SVM)
• Example AI Tools:
• TensorFlow
• Scikit-learn

Step 4: Model Training

Train the model using labeled datasets of phishing and legitimate emails.

• Utilize cross-validation techniques to enhance model accuracy.

Step 5: Model Evaluation

Evaluate the model’s performance using metrics such as:

• Accuracy
• Precision
• Recall

Example AI Tools:

• Google Cloud AutoML
• IBM Watson Studio

Step 6: Deployment

Deploy the trained model into the email security system.

• Integrate with existing email platforms using APIs.
• Example Products:
• Microsoft Defender for Office 365
• Proofpoint Email Protection

Step 7: Continuous Monitoring

Monitor the system for new phishing threats and model performance.

• Utilize anomaly detection algorithms to identify unusual patterns.
• Example AI Tools:
• Darktrace
• CylancePROTECT

Step 8: User Training and Awareness

Conduct regular training sessions for end users on identifying phishing attempts.

• Utilize simulated phishing attacks to reinforce learning.

Step 9: Feedback Loop

Gather feedback from users and stakeholders to improve the system.

• Adjust AI models and workflows based on feedback and new threats.

4. Conclusion

This workflow ensures a robust automated phishing detection and email security system, leveraging AI tools and continuous improvement strategies.