Masergy’s Global DataGuard Awarded Patent for Adaptive Behavioral Intrusion Detection System

Masergy’s Global DataGuard Awarded Patent for Adaptive Behavioral Intrusion Detection System

Behavior-Based Security Technology Addresses Big Data Problems

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Addison, Texas – July 17 – 2012 – Global DataGuard®, the premier provider of network behavior analysis-based (NBA) Unified Enterprise Security™ (UES) and Unified Enterprise Cloud Security™ (UECS), today announced they have achieved patent certification for Adaptive Behavioral Intrusion Detection Systems and Methods. The patent discloses critical systems and methods for analyzing historical network traffic and determining which traffic does not belong in a network.

Global DataGuard’s network behavior analysis, provided as the Behavioral Correlation Module (BCM) within the UES security suite, is continuously performed over long periods of time, learning a multitude of behaviors within networks or information systems and generating alerts when abnormal or suspicious traffic occurs. The BCM intelligently forms correlations between disparate sources to find emergent behavior indicative of an advanced persistent threat or other suspicious changes to network traffic. Over time, behaviors are predictive, and the BCM attempts to predict outcomes, becoming proactive instead of just reactive.

“Intrusions occur throughout whole information systems, including network infrastructure, application servers, and user devices,” explained Scott Paly, CEO of Global Dataguard. “By treating the information system as a whole and performing network behavior analysis across it continually over time, the chances of detecting issues that signature or rules-based systems may miss are increased significantly.”

Big data analysis and correlation represents a massive leap in the way in which security professionals are now able to detect and prevent complex, evolving attacks that span over periods of time, or Advanced Persistent Threats (APTs). Monitoring and analyzing big data, the BCM can process huge amounts of data — 900 billion Mb daily on a large network in a continuous process that employs over 1200 algorithms. The primary data source is raw network traffic data, but also incorporates IDS alerts, scans, SIEM alerts and policy violations in the analysis. Global DataGuard has successfully prevented and detected the APT type of attack for over 10 years.

Global DataGuard’s UES is the industry’s first truly integrated, network behavior analysis and correlation-based security platform, combining the unique integration properties of a security architecture with the adaptive and predictive analysis, data sharing, tracking and analysis capabilities of a network behavior analysis and correlation engine with intrusion detection and prevention; vulnerability scanning and management; log management, analysis and monitoring; network access and policy monitoring; and comprehensive threat management for prioritized network, global and vendor threats and vulnerabilities – within a multilayered architecture that spans premise-based, cloud and hybrid network environments.