Faced with the ever-evolving nature of DDoS attacks, a single defense method is unlikely to be permanently effective. The goal of Japan's high-defense servers isn't to completely block all incoming traffic. Instead, they employ a layered, controllable, and intelligent defense system to prevent attack traffic from impacting service availability and user experience. Practice has proven that successfully neutralizing DDoS attacks relies on four key elements: rapid and accurate detection, network-level traffic cleaning, transport and session protection, and intelligent filtering at the application layer. The following article details how to neutralize DDoS attacks on Japan's high-defense servers, focusing on practical technical measures and operational processes.

The first step is to establish a high-speed, low-false positive detection system. Promptly detecting and accurately characterizing attacks is the prerequisite for all subsequent actions. Detection should be based on three dimensions: traffic anomalies, connection behavior, and application request characteristics. Common approaches include rate and packet count thresholds at the network interface card and switch layers, NetFlow/sFlow export combined with traffic analysis tools, and request pattern analysis at the web layer. Using Prometheus or ELK to collect bandwidth, connection counts, request rates, and status code distribution, and setting multi-level alert thresholds, automatic or semi-automatic responses can be triggered at the early stages of an attack. An example command for deploying traffic threshold alerts (using vnstat or iftop for a quick check) is as follows:

vnstat -i eth0 --oneline

Upon detecting an anomaly, it's crucial to immediately determine the attack type (bandwidth exhaustion, half-open SYN/ACK, UDP flood, slow HTTP, or HTTP flooding), as different attack types require different strategies. For quick identification, use mtr/traceroute to determine if the issue is at the link layer, and use tcpdump to capture packets and confirm protocol characteristics:

tcpdump -i eth0 -c 200 -w /tmp/attack.pcap

The second step is to build a network-layer and carrier-grade defense chain. Japan's high-defense solution is fundamentally based on upstream bandwidth and scrubbing capabilities. Partnering with trusted Japanese IDCs or cloud providers and pre-configuring traffic diversion to scrubbing centers and anycast networks is key to combating high-volume attacks. In the event of a high-volume attack, the target IP address is forwarded to a scrubbing device or cloud at the BGP level. The scrubbing center removes malicious packets based on the five-tuple, rate, packet length, and abnormal patterns before forwarding legitimate traffic. The basic process for coordinating BGP traffic forwarding with upstream traffic is typically provided by the IDC. Customers must pre-sign an SLA and configure a BGP community. The following is an example of a typical command (use with caution) for conducting a local blackhole test or temporary blocking:

ip route add blackhole 203.0.113.45/32

The third step is to implement transport layer and session protection on servers and edge devices. Common transport layer attacks include SYN floods, RST attacks, UDP floods, and TCP connection exhaustion. Countermeasures include enabling TCP SYN cookies, increasing kernel queue and half-open connection thresholds, using iptables/ipset for rate limiting, and implementing stateful connection limiting on edge devices. Kernel adjustments can significantly improve the system's resilience to attacks. Typical sysctl modifications are as follows:

sysctl -w net.ipv4.tcp_syncookies=1
sysctl -w net.ipv4.tcp_max_syn_backlog=4096
sysctl -w net.ipv4.tcp_fin_timeout=30

Combining iptables with ipset can achieve efficient blacklisting and rate control, especially in highly concurrent SYN/UDP attacks. ipset can be used to store a large number of malicious IP addresses and quickly match them at the kernel level:

ipset create blacklist hash:ip family inet
iptables -I INPUT -m set --match-set blacklist src -j DROP
iptables -A INPUT -p tcp --syn -m limit --limit 50/s --limit-burst 200 -j ACCEPT

Use Nginx or an L4 load balancer to control connections at the transport layer. For example, limit upstream backend pressure through proxy_protocol and connection pool configurations:

limit_conn_zone $binary_remote_addr zone=addr:10m;
limit_conn addr 10;

The fourth step is to implement high-precision application-layer filtering. Application-layer attacks such as HTTP floods, slow POSTs, and slow reads require signature recognition and behavioral analysis at the WAF or application edge. Deploying a Web Application Firewall (such as ModSecurity, Cloud WAF, or a commercial WAF) can block common injections and abnormal requests based on rules. Behavioral analysis based on rate, session behavior, User-Agent, and Referrer should also be implemented. The following is an example of Nginx's limit_req and limit_conn controls at the HTTP request level:

limit_req_zone $binary_remote_addr zone=req_limit:10m rate=30r/s;
server { location /api/ { limit_req zone=req_limit burst=60 nodelay; } }

The fifth step is to establish an automated and traceable response process. When an attack occurs, the response process should include: detection and confirmation, temporary mitigation (such as rate limiting, IP blocking, or traffic diversion), deep cleaning, regression testing, and post-mortem review. Scripted automated responses can implement initial mitigation within minutes. An example is using fail2ban to automatically block SSH or HTTP brute force requests:

fail2ban-client set sshd banip 198.51.100.23

However, automated responses must be manually reviewed and thresholded to avoid impacting normal business operations. After the attack, pcap, logs, and traffic metrics should be exported as evidence for a detailed review, rule updates, and weaknesses addressed.

The sixth step is to implement performance and resource redundancy to reduce the risk of a single node being compromised. Using Anycast, global load balancing, and multi-datacenter deployments can distribute the attack surface across multiple nodes. Combined with a CDN, static resources can be fully decentralized to edge nodes. Dynamic resource scaling combined with elastic cleanup ensures service availability during an attack. Deploying multiple zones and nodes, along with health checks and automatic failover, ensures uninterrupted user requests. A sample load balancing configuration (HAProxy) distributes traffic and performs health checks:

listen app
bind *:80
mode http
balance roundrobin
server s1 10.0.0.1:80 check
server s2 10.0.0.2:80 check

The seventh step is to strengthen logging, monitoring, and forensics capabilities. Timely traffic data, application logs, system logs, and BGP event logs are essential for post-incident analysis. Using a centralized logging system (ELK/EFK) and traffic analysis tools can quickly identify the cause and affected areas after an attack. Saving sufficient pcap and NetFlow data can help facilitate forensic collaboration with ISPs or legal agencies, and can be submitted to scrubbing services or law enforcement if necessary. Example of packet capture and storage:

tcpdump -i eth0 -w /var/log/attack-$(date +%F-%H%M).pcap

Finally, long-term defense requires integrating security into architecture and operational practices. This includes regularly rehearsing DDoS emergency response procedures, establishing collaborative channels with multiple scrubbing services and ISPs, implementing application protection coding and resource limits, and periodically updating WAF rules and blacklists. Drills should verify the end-to-end process from detection to scrubbing to recovery, and iterate thresholds and automation scripts based on drill results.

Japan's high-defense servers rely on multi-layered collaboration to neutralize DDoS attacks. First, bandwidth and BGP traffic diversion to scrubbing centers are prepared at the network edge; second, kernel tuning, rate limiting, WAF rules, and behavioral analysis are implemented at the server and application layers. Detection, temporary mitigation, deep scrubbing, regression, and review must be integrated into the operational loop, and automation and drills should be used to reduce false positives and response times.