Next-Generation Packet Analysis with Precision and Efficiency
NG Deep Packet Inspection utilizes advanced packet analysis algorithms and metadata extraction techniques to accurately identify applications and content within network traffic. By performing deep analysis from packet headers to payloads and examining the signals and patterns in communication traffic, it ensures precise classification of applications and protocols, even in encrypted traffic.
NG DPI technology performs in-depth analysis of network traffic to detect and block unknown threats, zero-day attacks, and encrypted malicious traffic in real time. Unlike traditional DPI, which operates on simple pattern matching, NG DPI enables more sophisticated threat detection through deep packet analysis, effectively countering advanced cyberattacks.
With encrypted traffic now constituting the majority of internet traffic, the ability to analyze encrypted data has become crucial. NG DPI technology can inspect TLS/SSL-encrypted traffic, detecting hidden malware and data leaks. This capability allows organizations to identify and mitigate threats within encrypted communications, significantly enhancing overall security.
NG DPI integrates closely with various security solutions, such as Security Web Gateway (SWG), Cloud Access Security Broker (CASB), and Zero Trust Network Access (ZTNA), to provide comprehensive and multidimensional security. The deep packet analysis insights from NG DPI are delivered in real time to these solutions, enabling precise visibility and policy enforcement for web traffic, cloud applications, and network access.
Through metadata inspection, all incoming traffic is analyzed and classified in real time. The traffic undergoes processing by six modules that analyze network, event type, OS, application, attributes, and protocol information. This process enables detailed identification of traffic sources, destinations, user IDs and sessions, protocols, application types, and attributes such as video, text, and voice, ensuring precise application recognition. This technology goes beyond basic traffic filtering, rapidly and accurately identifying approximately 3,000 network applications and 500 protocols, even in SSL/TLS-encrypted traffic or complex multi-protocol environments.
As more protocols and applications, such as Skype, Facebook, Twitter, and Dropbox, adopt encryption, accessing payloads or content directly has become increasingly challenging. MONITORAPP's NG DPI addresses this by leveraging packet size, timing, latency, throughput, behavior, and statistical analysis to effectively extract protocol and application information, even from encrypted traffic. For instance, video streams exhibit distinct characteristics, such as a saw tooth buffering pattern, unlike the stable throughput pattern of file downloads. This advanced analysis enables precise threat detection beyond simple traffic filtering, ensuring accurate identification of threats in SSL/TLS-encrypted traffic and complex multi-protocol environments.
Through metadata inspection, all incoming traffic is analyzed and classified in real time. The traffic undergoes processing by six modules that analyze network, event type, OS, application, attributes, and protocol information. This process enables detailed identification of traffic sources, destinations, user IDs and sessions, protocols, application types, and attributes such as video, text, and voice, ensuring precise application recognition. This technology goes beyond basic traffic filtering, rapidly and accurately identifying approximately 3,000 network applications and 500 protocols, even in SSL/TLS-encrypted traffic or complex multi-protocol environments.
As more protocols and applications, such as Skype, Facebook, Twitter, and Dropbox, adopt encryption, accessing payloads or content directly has become increasingly challenging. MONITORAPP's NG DPI addresses this by leveraging packet size, timing, latency, throughput, behavior, and statistical analysis to effectively extract protocol and application information, even from encrypted traffic. For instance, video streams exhibit distinct characteristics, such as a saw tooth buffering pattern, unlike the stable throughput pattern of file downloads. This advanced analysis enables precise threat detection beyond simple traffic filtering, ensuring accurate identification of threats in SSL/TLS-encrypted traffic and complex multi-protocol environments.
AIOS Platform
Provides highly optimized application security with high-speed traffic classification and delivery technology
Proxy Technology
Provides stable and high-level inspection for application security
Sandbox Technology
Detects unknown threats by analyzing suspicious content in an isolated virtual environment
Profiling Technology
Utilizes profiling techniques to block unknown attacks and automatically establish complex security policies
Identifies applications through advanced packet analysis and metadata extraction
Provides security solutions in the form of as-a-service through global edge infrastructure
Provides secure network environments through Zero Trust-based authentication in non-face-to-face and cloud environments
Provides valuable security information by analyzing and sharing threat data using AI/ML