Many people encounter a seemingly simple yet easily misjudged problem: a sudden surge in server traffic – is this due to business growth or an attack? Especially in high-bandwidth servers, overseas nodes, or cross-border business scenarios, simply relying on "traffic volume" is no longer sufficient for effective judgment. Truly valuable judgment comes from understanding the "behavior itself" of the traffic, rather than over-reliance on a single metric.

　　Essentially, the fundamental difference between normal business traffic and attack traffic lies not in quantity, but in whether it "serves a clear business objective." Normal traffic exists purposefully; it always revolves around specific functions, pages, or interfaces, and its correlation can be found in access logs, application logic, and user behavior. Attack traffic, on the other hand, is not intended to complete business actions but rather to consume resources, create congestion, or trigger anomalies, thus often lacking a reasonable business motivation.

　　In normal business scenarios, traffic growth is usually predictable. For example, promotional activities, content releases, and peak user periods all lead to a gradual increase in traffic. This growth often presents a relatively smooth curve, and even sudden peaks are usually highly correlated with a specific event. Attack traffic is more like an "external shock," often erupting suddenly in a very short time. Its traffic curve is steep and inconsistent with historical patterns, sometimes even jumping from low load to full load within seconds.

　　From the perspective of access paths and request content, normal business traffic has a clear logical structure. The URLs, parameters, and method types of requests are highly consistent with the application design. For example, page accesses are concentrated on real paths, API calls conform to the interface documentation, and the request order matches user habits. Attack traffic, on the other hand, often exhibits highly repetitive and context-deficient request behavior, such as continuously requesting the same resource, repeatedly triggering non-existent paths, or making meaningless repeated calls to a single interface within a short period.

　　Connection behavior is also a very intuitive distinguishing feature. Normal user access typically establishes a limited number of connections with relatively reasonable connection lifecycles and natural time intervals between requests and responses. Attack traffic, however, is often accompanied by an abnormal surge in the number of connections. Either a large number of short connections are established and quickly disconnected, or a large number of "half-open" or "slow" connections are maintained, consuming server session resources without completing valid requests. Such behavior is highly destructive at both the application and system layers, but is almost impossible for real users to experience.

　　From a source distribution perspective, normal business traffic often exhibits relatively concentrated geographical and network characteristics, at least statistically matching the target user group. Even cross-border business shows certain stable source proportions. Attack traffic, on the other hand, typically has highly dispersed source characteristics, with a large number of IPs originating from different countries, different ASs, and even changing constantly within a short period. This distribution pattern is not accidental, but rather a way to circumvent simple blocking and rate limiting strategies.

　　Protocol and packet characteristics are also worth noting. Normal business traffic mostly follows conventional protocol usage patterns, with packet size and interaction frequency within reasonable ranges. Attack traffic may use a large number of abnormal protocol combinations, extreme packet sizes, or malformed packets. For example, in a UDP attack, the server may receive a large number of packets completely unrelated to business operations. This traffic consumes a lot of resources at the network layer but leaves no meaningful trace in the application logs.

　　Another easily overlooked but highly valuable criterion is the relationship between system resource consumption and business metrics. Under normal circumstances, increased traffic is usually accompanied by synchronous changes in metrics such as CPU utilization, memory usage, and the number of successful business requests. However, in attack scenarios, resource consumption and effective business metrics are often severely mismatched. For example, CPU usage may spike but order numbers may be zero, or bandwidth may be fully utilized but page views may barely increase. This "input-output imbalance" is one of the most typical signals of attack traffic.

　　In terms of continuity and rhythm, normal business traffic is more elastic, fluctuating with changes in user behavior and exhibiting clear diurnal patterns and usage cycles. Attack traffic, on the other hand, often lacks this natural rhythm, either continuously operating at high pressure or repeatedly appearing at a fixed frequency, exhibiting obvious automated characteristics. This "mechanical" traffic behavior is very easy to identify in long-term monitoring.

　　It is important to emphasize that in the real environment, there is no absolutely pure "normal" or "attack" traffic. Web crawlers, scanners, misconfigured programs, and malicious but low-intensity consumption behaviors often fall somewhere in between. This is why judging based on a single characteristic is highly prone to false positives or false negatives. The truly effective way to differentiate between normal and attack traffic is to analyze traffic behavior within its business context, examining its rationality, necessity, and explainability.

　　In terms of response strategies, understanding the significance of this difference is not merely about "determining whether an attack has occurred," but more importantly, about deciding on the appropriate course of action. Normal business traffic requires scaling, optimization, and scheduling, while attack traffic requires identification, restriction, and cleansing. Treating normal traffic as an attack could directly harm the business; conversely, treating attack traffic as business growth can have equally serious consequences.

　　Therefore, distinguishing between normal and attack traffic actually tests the depth of understanding that operations and security teams have of their own business. Only when you sufficiently understand what is "normal" can you make accurate judgments quickly when anomalies occur. This ability does not come from a single security product, but from long-term observation, analysis, and accumulated experience.