Transform your email security with Barracuda’s AI
Using AI for email security requires expertise in machine learning, data science, and deep knowledge of email threats. Barracuda was first with AI for email security in 2017.
Integration with Microsoft 365
Fast deployment with no MX records changes required. Immediate access to a large volume of historical email data.
- Email data ingestions — API-based integration with Microsoft 365 ingests large amounts of historical email data, serving as the foundation for training the AI model.
- Threat data platform — Shared threat intelligence data is sourced from across products to improve accuracy and speed of detection. Partnerships with third parties further improve the volume and quality of data.
Train AI models
Email data is used to train Barracuda’s AI models to recognize patterns and behaviors associated with different types of emails, both benign and malicious.
- Communication graph creation — AI algorithms create a communication graph for each user within your organization, relying on email metadata such as email addresses, domains, and IP addresses as well as relationships or interactions between these entities.
- Data privacy and compliance — Handling email data with care is essential, especially if it contains sensitive or personal information. We ensure compliance with data privacy regulations and implement necessary safeguards to protect your data integrity and privacy. Visit our trust center for more information.
Real-time analysis
Barracuda AI relies on content analysis, anomaly detection, and natural language processing to scrutinize all aspects of the email for malicious intent.
- Natural language processing (NLP) — The AI analyzes content of incoming messages for sentiment, context, tone, and potentially malicious intent.
- Pattern recognition — The AI identifies known phishing patterns and signatures, allowing it to swiftly recognize and flag suspicious emails.
- Anomaly detection — Beyond known patterns, AI looks for anomalies in email behavior and characteristics. It identifies irregularities in sender behavior, unusual email content, or deviations from established communication patterns.
Threat remediation
Barracuda AI continuously monitors incoming messages for signs of threats such as phishing or impersonation and takes automated remediation actions to quarantine or delete malicious emails.
- Automated remediation — Depending on the severity and type of threat, AI can take automated remediation actions, such as deleting or redirecting suspicious emails to a junk folder.
- User alerting and education — AI will generate real-time alerts to notify users and security teams of an attack. These alerts can include information on the nature of the threat and recommended actions.
Continuous learning
AI continually learns and adapts to new threats. As new data becomes available, its models and heuristics are automatically updated to improve the accuracy of detection.
- Feedback loop — Feedback from user-reported emails and security analysts' insights is automatically used to retrain Barracuda AI models to improve their performance over time.
- Lower false positives — The continuous and self-learning nature of Barracuda AI improves over time by fine-tuning email security, reducing the risk of false alarms and minimizing disruptions for legitimate users.
Stay ahead of the most advanced email threats
Self-learning
Autonomously identifies new attack patterns and refines detection algorithms without requiring manual intervention. This dynamic self-improvement not only enhances threat detection accuracy but also frees up valuable human resources by minimizing the need for constant rule configuration and updates.
Explainable AI
Gain transparency and clarity into the decision-making processes of AI models, allowing security teams to understand not just that a threat has been detected, but also why and how. This also plays a pivotal role in enhancing your threat detection and incident response.
Superior detection efficacy
AI will automatically update and improve its threat detection algorithms based on new data. This allows your organization to maintain a proactive and adaptive defense against evolving email threats, and it makes the solution exceptionally accurate at detecting attacks.
