How AI‑Powered Firewalls Outperform Traditional NGFWs in Detecting Advanced Threats

Why AI Firewalls Are Needed

Gartner defined NGFW in 2009 as a deep‑inspection firewall that integrates application identification, IPS, and anti‑virus functions. After more than a decade, the rapid growth of cloud, mobile, and IoT environments has produced a surge of advanced and variant threats that static signature databases cannot keep up with.

Signature‑based detection cannot handle advanced, unknown threats – signatures only describe known malware and have limited capacity, leading to high false‑positive rates and delayed response to novel attacks.

Threats are multi‑layered, encrypted, and harder to block with signatures alone – IoT expansion has increased internal threats, and attackers now use full attack chains and encrypted channels that signature matching cannot fully inspect.

Manual threat remediation is time‑consuming and costly – administrators must constantly adjust policies, analyze logs, and respond to incidents, which depends heavily on skill level and consumes significant operational effort.

Differences Between AI Firewall and Traditional NGFW

While NGFWs rely on static rule sets, AI firewalls replace pure signature matching with intelligent detection engines that train threat models on massive sample data and continuously optimize them using real‑time traffic. This shift requires dedicated hardware to provide the necessary compute power.

How AI Firewalls Detect Advanced Threats

The core of the AI firewall is its intelligent detection engine, which uses machine‑learning models to identify sophisticated attacks.

Cloud‑side sample training (supervised learning) – Millions of traffic samples are processed in the cloud to build detection models, which are then pushed to the firewall for real‑time inspection.

On‑premise learning (unsupervised learning) – The firewall continuously learns from live network traffic on the device, adapting to new patterns without explicit labeling.

Both training methods generate models that can detect frequent malware variants, compromised hosts, encrypted data exfiltration, slow‑rate and distributed brute‑force attacks. Updated models are delivered to the firewall without requiring a full software upgrade.

AI Firewall Attack‑Chain Interception

External infiltration stage – Phishing emails or USB devices deliver malicious files to the internal network; the AI firewall uses intelligent malicious‑file detection algorithms to extract file features, greatly improving detection rates compared with signature‑based methods.

Attacker‑to‑compromised‑host communication – Compromised hosts communicate with C&C servers via encrypted channels; the AI firewall provides C&C outbound detection and DGA domain detection, and can identify malicious encrypted traffic without decryption.

AI Firewall Product Line

Huawei launched the mid‑range AI firewall USG6000E series in 2018 and later introduced the high‑end USG12000 series. Both series embed the intelligent detection engine, support encrypted‑traffic threat inspection without decryption, and include dedicated hardware accelerators to achieve high detection performance.