The Domain Name System (DNS) is the foundation of cyberspace, and traditional, single-point DNS protection methods are proving inadequate against increasingly complex and sophisticated attacks. Modern DNS security solutions are building a resilient DNS system through a systematic architecture, intelligent technologies, and end-to-end governance, enabling proactive responses and rapid recovery.

The primary shift in building a modern DNS security system is from simply piling up isolated technical products to a multi-layered defense encompassing core, architecture, and governance. At the core security level, the key is to ensure the DNS resolution engine's autonomy, controllability, and high reliability, guaranteeing stable operation of basic resolution services under any circumstances and preventing data tampering. This requires the DNS software itself to possess strong anti-attack capabilities and a comprehensive data integrity verification mechanism.

At the architecture security level, adhering to the principles of "separation and convergence" is crucial. By separating authoritative and recursive resolution, and separating business and management planes, risks can be effectively isolated, limiting the scope of attack impact. Simultaneously, employing technologies such as anycast to horizontally converge service IPs can distribute traffic across multiple nodes globally, mitigating large-scale distributed denial-of-service attacks.

At the system security level, the goal is to shift from passive response to proactive control. This requires continuous monitoring, analysis, and prediction of the usage status of all domain names across the network, and standardized processes for the application, allocation, and revocation of domain name resources, thereby proactively eliminating security risks through management. For example, large enterprises often need to manage multiple DNS systems from different cloud service providers, and the complexity and inconsistency of their configurations are themselves significant sources of risk. Therefore, a status management solution that can provide a unified visual view and monitor configuration errors, expired certificates, or violation records in real time has become a necessity for enterprise security operations.

Faced with massive, low-frequency, and covert new types of attacks, detection methods based on fixed rules are no longer sufficient. Modern DNS security solutions rely heavily on big data and artificial intelligence technologies to achieve real-time threat perception and intelligent handling.

Full traffic collection and real-time analysis are the foundation of all this. By deploying collection devices at key network nodes, complete raw DNS traffic data is obtained, providing real-world material for subsequent analysis. Subsequently, using a "stream-batch integrated" data processing architecture, the needs of real-time early warning and in-depth retrospective analysis can be met simultaneously. The streaming computing framework can process data at the millisecond level, detecting anomalies in real time; batch processing can perform correlation mining on historical data to reveal complex attack chains. This architecture enables security teams to quickly block ongoing attacks and, through full data backtracking, create a complete attack profile, facilitating threat attribution.

The application of advanced threat detection algorithms significantly improves identification accuracy. For example, to combat "slow" DDoS attacks—where tens of thousands of bot nodes initiate queries at extremely low frequencies but converge into a torrent—advanced protection systems incorporate algorithms such as "response entropy detection." This algorithm identifies anomalies by analyzing the distribution of response types and record types returned by DNS servers. Massive random domain name queries initiated by attackers typically result in an abnormally high proportion of "domain does not exist" responses, which are accurately identified by the entropy model, even if the individual query frequency appears perfectly normal. Simultaneously, utilizing the EDNS extension of the DNS protocol allows for the transmission of richer contextual information, such as client subnets, enabling the protection system to more accurately distinguish between legitimate users and attack traffic, avoiding false positives on a large number of legitimate users passing through the same gateway.

True DNS security lies not only in the resolution service itself but also throughout the entire chain from domain registration to final access. Recent major global network outages serve as a stark reminder that oversights in the registration and management process can lead to catastrophic consequences. Therefore, "Resilient DNS" emphasizes safeguards across the entire chain.

This includes strengthening compliance audits and risk monitoring during registration to prevent malicious domain registration. In the resolution phase, in addition to the aforementioned protective measures, the promotion of DNSSEC (Domain Name System Security Extension) technology is crucial. DNSSEC ensures that DNS responses are not tampered with during transmission through digital signatures, fundamentally defending against cache poisoning attacks and serving as a core protocol for ensuring data integrity. Furthermore, building a multi-site, multi-active disaster recovery system to ensure second-level switching and rapid recovery in the event of any node failure is also key to building business continuity.

Looking ahead, the development of DNS security will be deeply intertwined with new technology scenarios. On one hand, the trend of "AI for DNS" is evident, leveraging artificial intelligence to enhance DNS's threat prediction, intelligent scheduling, and automated handling capabilities. On the other hand, "DNS for AI" has become a new mission, requiring the next generation of DNS to evolve into a critical infrastructure supporting computing networks and AI applications. For example, in complex computing power scheduling scenarios, DNS needs to be able to intelligently direct requests to the most suitable computing resources, which places unprecedentedly high demands on its resolution intelligence, low latency, and security.