As cyber threats become more automated, evasive, and nation-state backed, security teams are increasingly turning to artificial intelligence (AI) and machine learning (ML) to stay ahead. But even the most sophisticated algorithms are only as effective as the data they consume.
At NetQuest Corporation, we’ve designed the new SNS2000 Streaming Network Sensor to serve a vital role in AI-enabled cyber defense: delivering the high-fidelity, protocol-enriched metadata that fuels modern threat detection models.
Why AI Needs Better Network Data
Security vendors and government agencies are increasingly embedding AI into their cyber toolchains, using it for everything from anomaly detection and user behavior analytics to automated incident response. However, these systems often struggle when data quality, structure, or visibility is insufficient. That’s where the SNS2000 makes a critical difference.
It ingests up to 1.6 Tbps of raw network traffic from high-speed links and performs real-time Deep Packet Inspection (DPI) to extract protocol-specific metadata. Rather than sending raw packets to an analytics engine or SIEM, the SNS2000 outputs AI-ready structured data—ideal for machine learning pipelines and behavioral models—streamlining the process with metadata that reveals the who, what, when, where, and how of every network session.
Structured Metadata: The Foundation for Smarter AI
Metadata is no longer just a byproduct of traffic monitoring—it’s the fuel that drives modern cybersecurity intelligence. The SNS2000 extracts critical elements such as:
- Application-layer protocol insights (HTTP, DNS, SIP, etc.)
- Session durations, byte counts, and flow directions
- Indicators of anomalous behavior or malformed traffic
- Visibility into encrypted traffic flows (without decryption)
This structured data empowers AI models to detect zero-day attacks through behavioral analysis, identify and correlate command-and-control activity, recognize signs of data exfiltration or lateral movement, and reduce false positives with context-rich insights.
Designed for Integration into AI-Driven Pipelines
Whether your AI solution lives in a SIEM, a data lake, or a real-time decision platform, the SNS2000 is built for seamless integration. Metadata streams are delivered in open formats compatible with:
- ML-based threat detection engines – Enabling AI models to detect sophisticated attacks, including zero-days and advanced persistent threats, by feeding them clean, structured, and high-fidelity network metadata.
- Behavioral analytics systems – Providing the session-level insights needed to identify unusual patterns in user or device behavior, helping to flag insider threats, compromised accounts, and other subtle anomalies.
- Security Orchestration, Automation, and Response (SOAR) platforms – Accelerating incident response by delivering enriched metadata that can trigger automated workflows and streamline triage, investigation, and mitigation.
- Government-grade cyber intelligence frameworks – Supporting national security and law enforcement operations with scalable, protocol-specific metadata essential for lawful intercept, threat attribution, and strategic intelligence gathering.
By delivering precise, relevant, and scalable data, the SNS2000 acts as a force multiplier for your existing cybersecurity investments.
Unlocking Proactive Defense at Scale
The cybersecurity landscape demands a shift from reactive to proactive defense—and that shift is powered by AI. But AI alone doesn’t win battles. It needs deep network intelligence to succeed.
The NetQuest SNS2000 is the bridge between raw traffic and actionable insight. It empowers cyber defenders to see more, know more, and act faster—with confidence that their AI engines are operating on the most complete and relevant data possible.
Ready to learn how the SNS2000 fits into your AI-driven threat detection strategy? Schedule a demo or download the product brief to explore how next-generation network sensors are redefining visibility at terabit scale.