CDN
How to Respond to DDoS Attacks? A practical guide to enterprise-grade traffic cleaning and global CDN protection
PublishedViews0EditorSudun TeamEstimated reading time 16 min
In 2026, global Internet attack traffic has entered the "Tbps era". According to the latest cybersecurity report, the peak DDoS attack bandwidth recorded last year was as high as 31.4 Tbps, and the attack frequency increased by more than 160% year-on-year. At the same time, the attack method has shifted from a single traffic type to a multi-vector composite strike. Attackers often launch slow wars of attrition against the application layer while launching network layer floods, leaving traditional defenses at the expense of one side and the other.
For any business that relies on the internet for business, DDoS attacks are no longer a question of "will happen" but "when and on what scale". When attack traffic easily exceeds data center egress bandwidth, and when hardware firewalls are rendered ineffective in the face of link saturation, organizations must look for new defense paradigms. Globally distributed CDN (content delivery network) architecture is the de facto standard for defending against large-scale DDoS attacks due to its natural decentralization, edge computing capabilities, and vast bandwidth reserves.
This article will systematically analyze the nature and types of DDoS attacks, deeply analyze how CDNs can deal with these threats through a three-layered defense-in-depth system, and provide practical cases and selection guidelines to help technical decision-makers build a robust enterprise security defense line.
A DDoS (distributed denial-of-service) attack is when an attacker uses multiple controlled computers (often referred to as "zombie hosts" or "broilers") to send a large number of legitimate requests to a target server, service, or network at the same time, consuming the bandwidth, computing resources, or application connections of the target system, resulting in normal users being unable to access the service.
Unlike traditional DoS (Single Source Denial of Service) attacks, DDoS utilizes a distributed architecture with thousands of attack sources that are extremely difficult to mitigate by simply blocking a single IP. Attackers infect a large number of IoT devices, PCs, or servers with malware, forming botnets that launch a flood of attacks on specific targets under unified commands.
Purpose and impact of DDOS attacks
DDoS attacks can be used for various purposes:
Ransomware: Attackers launch a small-scale attack and then send a ransom email demanding a ransom to stop the attack.
Business competition: Attacking competitors during promotional activities and new product launches, causing the other party's service to be paralyzed and seizing market share.
Political protests: Attacks on government, media, or corporate websites to express political stances.
Distraction: As a prelude to more sophisticated attacks (e.g., data theft, malware planting), DDoS keeps security teams busy responding and masking the real intrusion.
Regardless of the motive, the consequences of DDoS attacks are severe: business disruption leads to direct financial losses, damage to brand reputation, loss of customers, and even regulatory penalties. For industries such as e-commerce, finance, gaming, etc., every minute of downtime can cost hundreds of thousands of dollars.
Depending on the network layer the target is in, DDoS attacks are typically divided into three categories: network layer attacks (L3/L4), application layer attacks (L7), and protocol attacks in between. Understanding these types is a prerequisite for choosing the right protection strategy.
2.1 Volumetric Attacks
Goal: Consumes the bandwidth of the target network, causing link congestion.
Principle: Sending a large number of data packets to the destination makes it impossible for network devices or links to handle legitimate traffic.
Common Types:
UDP Flood: A large number of UDP packets are sent to a random port of the target, and the target system checks whether an application is listening to the port.
ICMP Flood: Sends a large number of ICMP Echo requests (ping packets) to force the target to reply, taking up bandwidth and CPU.
Reflection amplification attack: The attacker forges the source IP as the victim's IP and sends small requests to vulnerable public services (such as DNS, NTP, Memcached), and the large responses returned by these services are sent to the victim, amplifying the traffic by tens or even hundreds of times.
2.2 Protocol Attacks
Target: Consumes the connection processing power of a server or network device (firewall, load balancer).
Principle: Exploit vulnerabilities in protocol implementation to maintain a large number of semi-connected or invalid connections to the target, exhausting system resources.
Common Types:
SYN flood: An attacker sends a large number of TCP SYN requests without completing the triple handshake, causing the server to maintain a large number of half-open connections and exhaust the connection table.
ACK Flood: Sends a large number of TCP ACK packets that force the server to check the connection status, consuming CPU.
fragmented packet attacks: Send malformed IP shards that crash when the target is reassembled.
2.3 Application Layer Attacks
Goal: Exhaust the compute resources (CPU, memory) of a web server, database, or application.
Principle: Simulate real user requests and send seemingly legitimate HTTP/HTTPS requests, but with extremely high frequency or request complex resources (such as search, login, report generation), making the application unable to respond to normal users.
Common Types:
HTTP Flood: A large number of GET/POST requests targeting specific URLs (such as homepages, API interfaces).
Slowloris: Slow attack, keep the connection to the server as long as possible, send data slowly, and take up the number of connections.
DNS Query Flood: Sends a large number of domain name resolution requests to DNS servers, exhausting DNS service resources.
CC Attack (Challenge Collapsar): Refers to resource consumption attacks targeting the web application layer, often using proxy IPs or botnets to simulate human behavior.
Figure 1: Relationship between DDoS attack types and OSI models
OSI layer attack type attack target Typical example
L3 Network Layer Bandwidth Consumption Network Links UDP Flood, ICMP Flood, Reflection Amplification
L4 Transport Layer Protocol State Consumption Firewall/Server Connection Table SYN Flood, ACK Flood
L7 Application Layer Application Resource-Consuming Web Server/Database HTTP Flood, Slowloris, CC Attack
CDNs, while originally designed to speed up content distribution, have a distributed architecture that makes them a natural defense against DDoS. Understanding how a CDN works helps in understanding why it is effective against attacks.
3.1 Basic Architecture of CDN
CDNs consist of edge nodes (PoPs) distributed around the world, which cache the static content of websites (such as images, CSS, JS) and direct user requests to the node closest to the user, thereby speeding up access. What's more, CDNs act as reverse proxies, where all user traffic first reaches the edge of the CDN and is forwarded by the CDN to the origin server. This "middleman" role makes CDNs an ideal barrier for isolating attacks.
3.2 Core Advantages of CDN Protection against DDoS
Distributed traffic dilution: Attack traffic is directed to hundreds of nodes around the world, each under a fraction of the pressure, avoiding single point of link saturation.
Edge computing capabilities: Each node has traffic detection and cleaning capabilities, which can be dealt with near the source before attacks enter the backbone network.
Ultra-large bandwidth reserve: Aggregate the egress bandwidth of all nodes to form a petabyte-level defense pool to easily deal with Tbps-level attacks.
Origin server hiding: CDN exposes edge node IPs, and the real origin server IP is hidden, preventing attackers from directly attacking the origin server.
Caching and acceleration: Static content is directly responded to by edge nodes to reduce the load on the origin server, while dynamic requests are accelerated through intelligent routing, ensuring a good user experience even in the event of an attack.
3.3 Three-layer defense system in depth
Modern CDN protection DDoS typically employs a three-layered defense-in-depth strategy:
Layer 1: Network layer dispersion and near-source cleaning (to deal with high-traffic attacks)
Layer 2: Refined traffic cleaning (distinguishing between normal and malicious traffic)
Layer 3: Origin stealth and business continuity guarantee (ensure absolute security of the origin server)
Next, we will break down these two dimensions in detail and reveal how CDNs can gradually mitigate DDoS threats.
4.1 Anycast technical principle
Anycast is a network addressing and routing technology that allows multiple nodes with different geographical locations to use the same IP address. When a user accesses the IP, the BGP routing protocol automatically forwards the request to the node that is "closest" (usually measured by AS hops).
In CDN, all edge nodes claim the same service IP through Anycast. When an attacker launches a DDoS, attack traffic around the world is naturally distributed to different nodes by BGP routes. For example, attack packets from Europe are routed to European nodes, while those from Asia enter Asian nodes. This "natural diversion" eliminates any human intervention and achieves the first level of dilution of attack traffic.
4.2 Near-source cleaning: Eliminate threats at the source
Traditional cleaning solutions often divert traffic to centralized cleaning centers, which creates two problems: first, the flow needs to travel long distances, increasing delays; Second, the cleaning center itself may become a bottleneck. CDN near-source cleaning is different - each edge node has traffic detection and cleaning capabilities, and attack traffic is identified and discarded by the node closest to the attacker before entering the Internet backbone.
Traditional Wash Center Mode:
Attacker -> Internet backbone -> Centralized cleaning center -> Backbone network -> Origin server (high latency, backbone network congestion)
CDN Near-Source Cleaning Mode:
Attacker -> local CDN node (immediately clean) -> Only legitimate traffic passes through the private backbone -> origin server (low latency, clean backbone)
4.3 Load balancing and dynamic scheduling
When a node encounters a hyperscale attack, Anycast combined with intelligent scheduling can further distribute the pressure. By monitoring the real-time load of each node, the CDN control center can dynamically adjust the BGP routing policy and direct some traffic to nearby idle nodes. This "peak shaving and valley filling" mechanism ensures that even if a single node link is close to saturation, the overall service will not be affected.
Dispersing traffic is only the first step, and the real challenge lies in accurately distinguishing between malicious and legitimate traffic. CDN uses hierarchical cleaning technology to filter step by step from the network layer to the application layer.
5.1 Automatic suppression of network layer (L3/L4).
At the network layer, we face high-traffic, stateless flood attacks. Modern CDNs use machine learning to establish a traffic baseline model, analyze network-wide traffic characteristics in real time, and automatically identify anomalies.
SYN cookie: For SYN Flood, the edge node enables SYN cookies, does not save the half-open connection state, verifies the legitimacy of the handshake through encrypted information, and directly discards the attack packet that forges the source IP.
Rate limiting: Set dynamic rate thresholds for specific protocols (such as UDP and ICMP), and directly lose packets beyond that.
Vulnerability signature matching: Edge nodes identify and block such requests for known reflection amplification attacks (such as NTP Monlist and DNS ANY queries).
Key indicators: A good CDN can reduce network layer attack traffic by more than 90%, and the SYN Flood filtering rate reaches 99.9%, and the response time is in milliseconds.
5.2 Application layer (L7) AI behavior analysis
Application-layer attacks are harder to defend against because malicious requests look almost indistinguishable from normal requests. Modern CDNs introduce AI and behavioral analytics to identify anomalies from multiple dimensions.
Behavioral baseline: Establish a normal user profile for each domain name, including access frequency, page dwell time, mouse trajectory (if including JS buried points), HTTP header order, TLS fingerprint, etc. Malicious scripts often show their strength in these details.
Device fingerprinting: Collect client device information (browser version, screen resolution, font list, etc.) to identify requests from the same broiler cluster.
Human-machine challenge: For suspicious requests, edge nodes return JS challenges or verification codes. Normal browsers can quickly execute JS and return results, but simple crawlers cannot parse and time out directly.
Dynamic IP Blacklist: Combines global threat intelligence to update malicious IP databases in real time to block known attack sources.
During the "Double Eleven" period, an e-commerce platform successfully intercepted automated credential stuffing attacks on payment interfaces through CDN's AI protection, intercepting more than 2 million malicious requests in a single day, and controlling the manslaughter rate below 0.1%.
Protection level Attack type Core technology Protection effect
L3/L4 UDP Flood, SYN Flood, Reflection Amplification Anycast Distribution, SYN Cookie, Rate Limiting, Vulnerability Signature Attack traffic reduction by 90%+, SYN Flood filtering rate of 99.9%
L7 HTTP Flood, CC Attack, Crawler AI Behavior Analysis, JS Challenge, Captcha, Device Fingerprint CC Attack Interception Rate >99%, Manslaughter Rate <0.1%
Origin server stealth IP direct connection, 0Day origin server whitelist, two-way authentication, token authentication Reduce the risk of origin server exposure by 95%+
Even if most of the attack traffic is cleaned, attackers can still bypass the CDN and directly attack the origin server as long as the origin server IP is exposed. Therefore, source hiding is the last line of defense of the protection system.
6.1 Deep hiding of origin server IPs
CDN acts as a reverse proxy, and all user requests first reach the edge node, which then forwards them to the origin server. The origin server only needs to accept connections from the CDN node, so configure strict inbound rules on the firewall: only allow the CDN node's IP segment to access port 80/443 of the origin server. This way, even if an attacker discovers an origin IP through DNS history or scanning, they will not be able to connect directly because the origin firewall will reject traffic from non-CDN sources.
Furthermore, TLS two-way authentication can be enabled, requiring CDN nodes to provide client certificates to ensure that the connection source is trustworthy. The dynamic token mechanism rotates the origin access credentials every 5 minutes, further increasing the difficulty of attacks.
6.2 Business continuity guarantee
In the event of an attack, CDN also provides a variety of mechanisms to ensure that services are not interrupted:
Site-wide acceleration and caching: Even if the origin server is temporarily unavailable, CDN nodes can provide cached content (such as product pages and static resources) to maintain basic services.
Intelligent origin return: When the origin server responds slowly or times out, the CDN can automatically retry the backup origin server or downgrade the cached content to avoid users seeing 5xx errors.
One-click switching: When the origin server needs to be migrated or maintained, the origin server configuration can be modified through the CDN console, and the traffic transition is smooth without the user being aware.
During the peak attack period, a government cloud platform used Sudun CDN's escort mode to compress the DDoS identification time from 15ms to 0.8ms, maintaining 99.99% availability during the attack, ensuring the continuity of people's livelihood services.
7.1 Live streaming e-commerce
A leading live broadcast platform encountered an 800Gbps DDoS+CC hybrid attack at 0:00 on Double 11 in 2025. Attack traffic poured in instantly, targeting live streams and transaction interfaces. The Sudun Anti-DDoS CDN used by the platform relies on AI intelligent scheduling to mobilize global nodes for traffic cleaning within 0.5 seconds, which not only successfully resists attacks, but also reduces the access latency of North American users to 25ms through intelligent routing, ensuring the smoothness of live streaming and the stability of transaction links. In the end, the platform's GMV increased by 23% against the trend on the same day, achieving a win-win situation of security and growth.
7.2 Cross-border finance
A bank's cross-border payment system faces multiple challenges such as cross-border attacks, data leaks, and compliance audits. Traditional solutions struggle to balance safety and performance. After connecting to Sudun Anti-DDoS Pro CDN, the national secret algorithm and quantum encryption fusion technology are used to reduce the HTTPS handshake time from 25ms to 3ms. At the same time, zero trust access control effectively prevents supply chain penetration through 5-minute rotation of database dynamic tokens and third-party biometric secondary authentication. The intelligent routing jitter reduction function compresses the jitter rate of the London-Shenzhen financial line from 1.2% to 0.03%, ensuring the stability of cross-border transactions.
7.3 Government affairs platform
A government cloud has often suffered from unknown types of attacks and frequent service interruptions. After connecting to the Anti-DDoS Pro CDN, with the help of AI attack intent modeling, it can identify IP exploratory scanning behaviors in advance, automatically block high-risk IP segments before an attack occurs, and increase the interception rate of unknown threats from 35% to 79%. The near-source cleaning capability of edge nodes compresses the attack response time to 0.8 milliseconds, ensuring the stable operation of government services.
In the face of many CDN security service providers, technology decision-makers should not only look at the price or the claimed defense peak, but also deeply evaluate the following core indicators:
8.1 Manslaughter rate after cleaning
The manslaughter rate is the key to measuring the quality of protection. Overly aggressive tactics can intercept real users, leading to business losses. A good CDN can control the kill rate below 0.1% through AI behavior analysis and continuous tuning. It is recommended to require manufacturers to provide A/B testing when selecting models to observe the performance of a small part of real traffic under protection.
8.2 Global Node Coverage and Bandwidth Reserve
The number of nodes directly determines the defense capacity and near-source cleaning effect. The more nodes, the more evenly the attack traffic is diluted and the less pressure on the individual nodes. At the same time, pay attention to whether the geographical distribution of nodes covers the target market. The total bandwidth reserve (the sum of the egress bandwidth of all nodes) should reach the Pb level to calmly respond to Tbps-level attacks.
8.3 Technical Support and SLA Commitments
Attacks often occur in the early hours of the morning or on holidays, and 24/7 expert response is crucial. Review SLA terms to ensure clear availability guarantees (e.g., 99.99%) during an attack, and check third-party stress test reports to avoid mismatching nominal values with actual capabilities.
Evaluation dimensions Key points Ideal indicators Verification method
Defense capability Protection bandwidth scale, manslaughter rate, attack response time TB-level protection, manslaughter rate <0.1%, response < 1 second Third-party test report, historical attack data
Network coverage Global number of nodes, regional distribution, intelligent scheduling coverage target market, single-region multi-node redundancy node list, real-time monitoring demonstration
Technical support 7x24 hours on duty, expert intervention timeliness, 99.99% availability during SLA attacks≥ T+0 level response, contract terms, customer reviews
In the market, leading service providers represented by Sudun CDN not only perform well in the above indicators, but also provide 7x24 expert escort services, making it the trusted choice of many leading enterprises.
In today's world where Tbps attacks have become the norm and multi-vector attacks are becoming more and more complex, traditional single-point defenses have completely failed. Globally distributed CDNs are best practices for DDoS protection due to their natural distributed architecture, edge cleaning capabilities, and massive bandwidth reserves.
CDNs are not only acceleration tools but also moats for enterprise security. From Anycast to dispersed traffic, to AI-driven refined cleaning, to origin stealth and disaster recovery guarantees, modern CDNs have built a complete defense-in-depth system.
In the face of endless threats, choosing a CDN partner with strong network infrastructure, deep technology accumulation, and high-quality service support is a wise move for enterprises to ensure business continuity. Cybersecurity has no end, and only continuous evolution can be invincible in the new wave of attacks.
