Patented AI-Powered Threat Detection Platform Enhances Real-Time Email Security
Detecting, Characterizing, and Remediating Email-Based Threats in Real Time
U.S. Patent No.11,824,870
Abnormal has developed a patented, AI-native platform that proactively detects and stops email-based threats as they happen. This breakthrough technology uses advanced machine learning to understand how people across an organization typically communicate, then flags anything that seems out of the ordinary. By focusing on human behavior instead of static rules, Abnormal can uncover threats that traditional security tools often miss.
This diagram shows how email threats are detected using a system made up of the customer’s enterprise network and Abnormal’s threat detection platform. The platform monitors communications across the network to identify potential risks."
The Abnormal AI Advantage
What makes the AI in this patented system unique is its ability to continuously learn from past communications and apply that knowledge to new messages as they arrive. By analyzing behavioral traits—like how often a sender identity or email address is used—the AI can detect subtle anomalies that might indicate a threat.
Why This Matters
Traditional email security measures often rely on static rules and known threat signatures, which can be insufficient against evolving attack vectors. Abnormal Security's patented approach introduces a dynamic, behavior-based detection mechanism that adapts to new threats, providing a robust defense against sophisticated email attacks.
Meet the Inventor
Sanjay Jeyakumar
Sanjay Jeyakumar is the CTO and Co-Founder of Abnormal AI, where he also leads Research and Development. A veteran engineering leader with over 17 years of experience, Sanjay has consistently been at the forefront of innovation—building intelligent systems that solve complex problems at a massive scale.
Realizing that true AI-powered cybersecurity requires a deep understanding of normal user behavior, Sanjay pioneered a patented system that detects compromised email accounts through behavioral baselines and anomaly detection—an industry-first approach now protected under U.S. Patent No.10,911,489.
Under his technical leadership, Abnormal’s AI-native platform has redefined what's possible in threat detection and prevention—helping the company earn recognition as a Leader in the 2024 Gartner® Magic Quadrant™.
How Abnormal's Detection Engine Works Behind the Scenes
- Data Collection and Normalization: The platform aggregates data from various sources, including email metadata, content, and user interaction patterns. This data is then normalized to establish a baseline of typical behavior for each user and organization.
- Anomaly Detection via Machine Learning: Utilizing sophisticated machine learning algorithms, the system continuously monitors ongoing communications, comparing them against established behavioral baselines to identify deviations that may signify threats.
- Automated Threat Remediation: Upon detecting a potential threat, the platform can initiate automated responses, such as quarantining suspicious emails, alerting security personnel, or adjusting access controls to prevent further compromise.
