Fortinet FortiDDoS 1500F. Firewall latency: 50 µs. Heat dissipation: 1477 BTU/h. Storage media type: SSD, SSD capacity: 480 GB. Form factor: 2U. AC input voltage: 100-240 V, AC input frequency: 50/60 Hz, Input current: 4.4 A
Distributed Denial of Service (DDoS) attacks remain a top threat to IT security and have evolved in almost every way to do what they do best: shut down access to your vital online services. Unlike intrusion and malware attacks, DDoS attackers have learned that they don’t need to attack only end-point servers to shut you down. They attack any IP address that routes to your network: unused IP addresses, Inter-router-link public IP addresses, or Firewall/Proxy/WiFi Gateway public IP addresses. Cloud-based CDN and DNS-based cloud mitigation cannot protect you from these attacks. What is the impact to your business if your users cannot reach cloud services because your firewall or demarc router public IP is being DDoSed? Your CDN-based web servers may be up but your business is down! Sophisticated multi-vector and multi-layer DDoS attacks use direct and reflected packets where the spoofed, randomized source IP addresses are impossible to ACL. These attacks are increasingly common as Mirai-style code has morphed into many variants and has been commercialized by providers of “stresser” sites. Anyone can call down large attacks for a few dollars. To combat these attacks, you need a solution that dynamically protects a large attack surface.
A Different and Better Approach to DDoS Attack Mitigation FortiDDoS massively parallel machine-learning architecture delivers the most advanced and lowest-latency DDoS attack mitigation on the market today, without the performance compromises normally associated with CPU-based systems. FortiDDoS inspects 100% of both inbound and outbound Layer 3, 4, and 7 packets, to the smallest packet sizes, resulting in the fastest and most accurate detection and mitigation in the industry. In place of pre-defined or subscription-based signatures to identify attack patterns, FortiDDoS uses autonomous machine learning to build an adaptive baseline of normal activity from hundreds-of-thousands of parameters and then monitors traffic patterns against those baselines. Should an attack begin, FortiDDoS sees the deviation and immediately takes action to mitigate it, often from the first packet.
